18 Jobs für Computational Linguistics in Schweiz

**Summary:**
Facebook is seeking Machine Learning Engineers to join our engineering team. The ideal candidate will have industry experience working on a range of classification and optimization problems like payment fraud, click-through rate prediction, click-fraud detection, search ranking, text/sentiment classification, collaborative filtering/recommendation, or spam detection. The position will involve taking these skills and applying them to some of the most exciting and massive social data and prediction problems that exist on the web.
**Required Skills:**
Software Engineer (Leadership) - Machine Learning Responsibilities:
1. Drive the team's goals and technical direction to pursue opportunities that make your larger organization more efficient
2. Effectively communicate complex features and systems in detail
3. Understand industry & company-wide trends to help assess & develop new technologies
4. Partner & collaborate with organization leaders to help improve the level of performance of the team & organization
5. Identify new opportunities for the larger organization & influence the appropriate people for staffing/prioritizing these new ideas
6. Suggest, collect and synthesize requirements and create an effective feature roadmap
7. Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules-based models
8. Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
**Minimum Qualifications:**
Minimum Qualifications:
9. Experience leading projects with industry-wide impact
10. Vast experience communicating and working across functions to drive solutions
11. Proven track record of planning multi-year roadmap in which shorter-term projects ladder to the long term-vision
12. Experience in driving large cross-functional/industry-wide engineering efforts
13. Significant experience in programming languages (Python, C++, Java, or R) with a technical background
14. Significant experience in mentoring/influencing senior engineers across organizations
15. Significant experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, NLP, data mining, or artificial intelligence
**Preferred Qualifications:**
Preferred Qualifications:
16. B.S. Computer Science or related technical field
17. Experience in shipping products to millions of customers or have started a new line of product
18. Experience with Hadoop/HBase/Pig or MapReduce/Sawzall/Bigtable/Hive/Spark
**Industry:** Internet

**Minimum qualifications:**
+ Bachelor's degree or equivalent practical experience.
+ 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
+ 1 year of experience implementing core machine learning concepts.
**Preferred qualifications:**
+ 1 year of experience with data structures or algorithms.
+ Ability to think of new creative approaches to problems and help our users.
+ Ability to develop new, user-facing products.
+ Excellent team-work spirit skills.
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
In Google Search, we're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
**Responsibilities:**
+ Conduct an in-depth analysis of model prompting/training and serving performance to find areas of efficiency while maintaining quality.
+ Collaborate with Research team partners in Google.
+ Develop web guide, a result-first AI experience for Search.
+ Focus on the quality aspects of the product this means prompting and distilling the latest Gemini models.
+ Write AI raters, running and analyzing evaluations, and launching improved versions of Web Guide.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also and If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form:

Description
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The AWS Industries Team at AWS helps AWS customers implement Generative AI solutions and realize transformational business opportunities for AWS customers in the most strategic industry verticals. This is a team of data scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and build applications to launch these solutions at scale. The AWS Industries team provides guidance and implements best practices for applying generative AI responsibly and cost efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
In this role you will be capable of using GenAI and other techniques to design, evangelize, and implement and scale solutions for never-before-solved problems.
Key job responsibilities
Design and implement complex, scalable, and secure AWS solutions tailored to customer needs.
Collaborate with stakeholders to gather requirements and propose effective migration strategies.
Providing technical guidance and troubleshooting support throughout project delivery.
Act as a trusted advisor to customers on industry trends and emerging technologies.
Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts.
About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences.
Mentorship and Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Basic Qualifications
3+ years of AI and ML experience and data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of cloud architecture and implementation.
Proven track record in designing and developing end-to-end Machine Learning and Generative AI solutions, from conception to deployment.
Experience in applying best practices and evaluating alternative and complementary ML and foundational models suitable for given business contexts.
Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.
Knowledge of data modeling principles, statistical analysis methodologies, and demonstrated ability to extract meaningful insights from complex, large-scale datasets.
Preferred Qualifications
AWS experience preferred, with proficiency in a wide range of AWS services (e.g., Bedrock, SageMaker, EC2, S3, Lambda, IAM, VPC, CloudFormation)
AWS Associate level certifications (e.g., Machine Learning Specialty, Machine Learning Engineer Associate, Solutions Architect Professional) preferred.
Experience with automation and scripting (e.g., Terraform, Python).
Knowledge of security and compliance standards (e.g., HIPAA, GDPR).
Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
Experience in developing and optimizing foundation models (LLMs), including fine-tuning, continuous training,and implementation of AI systems.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Description
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The AWS Industries Team at AWS helps AWS customers implement Generative AI solutions and realize transformational business opportunities for AWS customers in the most strategic industry verticals. This is a team of data scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and build applications to launch these solutions at scale. The AWS Industries team provides guidance and implements best practices for applying generative AI responsibly and cost efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
In this role you will be capable of using GenAI and other techniques to design, evangelize, and implement and scale solutions for never-before-solved problems.
Key job responsibilities
Design and implement complex, scalable, and secure AWS solutions tailored to customer needs.
Collaborate with stakeholders to gather requirements and propose effective migration strategies.
Providing technical guidance and troubleshooting support throughout project delivery.
Act as a trusted advisor to customers on industry trends and emerging technologies.
Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts.
About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences.
Mentorship and Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Basic Qualifications
PhD, or Master's degree and 5+ years of applied research experience
3+ years of building machine learning models for business application experience
Experience with programming in Java, Python or related language
Experience with neural deep learning methods and machine learning
Preferred Qualifications
Experience with LLM pre-training, fine-tuning, and evaluations
Familiarity with distributed training and acceleration method/implementation/library for LLMs or large-scale ML in general, e.g., DeepSpeed, Nemo-Megatron, PyTorch Lightning.
science backgrounds demonstrated by degrees in fields such as:
Mathematics
Statistics
Physics (various specializations)
Molecular Biology
Neuroscience
Experience manipulating large datasets using RDBMS or SQL-on-Hadoop technologies, and be familiar with machine learning or statistical libraries like SparkML, scikit-learn, caret, mlr, and MLlib
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Description
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The AWS Industries Team at AWS helps AWS customers implement Generative AI solutions and realize transformational business opportunities for AWS customers in the most strategic industry verticals. This is a team of data scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and build applications to launch these solutions at scale. The AWS Industries team provides guidance and implements best practices for applying generative AI responsibly and cost efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
In this role you will be capable of using GenAI and other techniques to design, evangelize, and implement and scale solutions for never-before-solved problems.
Key job responsibilities
Design and implement complex, scalable, and secure AWS solutions tailored to customer needs.
Collaborate with stakeholders to gather requirements and propose effective migration strategies.
Providing technical guidance and troubleshooting support throughout project delivery.
Act as a trusted advisor to customers on industry trends and emerging technologies.
Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts.
About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences.
Mentorship and Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Basic Qualifications
3+ years of AI and ML experience and data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience 3+ years of cloud architecture and implementation.
Proven track record in designing and developing end-to-end Machine Learning and Generative AI solutions, from conception to deployment.
Experience in applying best practices and evaluating alternative and complementary ML and foundational models suitable for given business contexts.
Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.
Knowledge of data modeling principles, statistical analysis methodologies, and demonstrated ability to extract meaningful insights from complex, large-scale datasets.
Preferred Qualifications
AWS experience preferred, with proficiency in a wide range of AWS services (e.g., Bedrock, SageMaker, EC2, S3, Lambda, IAM, VPC, CloudFormation)
AWS Associate level certifications (e.g., Machine Learning Specialty, Machine Learning Engineer Associate, Solutions Architect Professional) preferred.
Experience with automation and scripting (e.g., Terraform, Python).
Knowledge of security and compliance standards (e.g., HIPAA, GDPR).
Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
Experience in developing and optimizing foundation models (LLMs), including fine-tuning, continuous training,and implementation of AI systems.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

**The Position**
A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Roche.
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
**The Opportunity**
The Large Molecule Drug Discovery group within AI for Drug Discovery seeks exceptional researchers who have a demonstrated research background in protein design and protein structure prediction/analysis, machine learning, project execution, a passion for research collaboration and technical problem-solving, and a proven ability to implement ideas and develop and/or apply methods for large molecule drug discovery. The group provides a dynamic and challenging environment for cutting-edge, multidisciplinary research including access to heterogeneous data sources, close links to top academic institutions around the world, as well as internal Genentech Research and Early Development (gRED) partners and research units. Our mission is to develop and apply physics and machine learning based methods to design novel macromolecules with therapeutic potential. Researchers in this role will develop, manage, and apply computational approaches for large molecule property prediction and de novo generative design, leverage multi-modal data sources including protein structure, protein property, and next-generation sequencing (NGS) data towards portfolio impact.
You will play a pivotal role in supporting, applying, and advancing the next generation of large molecule generative machine learning models for drug discovery. We seek an individual who is not only passionate about teamwork and technical problem-solving but also has a proven track record of delivering innovative solutions in machine learning and protein engineering. Your responsibilities will include data preparation and cleaning, deploying both internal and external discriminative and generative models, and closely collaborating and communicating with colleagues in Genentech's antibody engineering department to engineer new antibody molecules using the lab-in-the-loop framework.
**In this role, you will:**
+ Develop and/or apply novel Computational Biology/Machine Learning methods to answer challenging research questions in LMDD.
+ Work with biological data from heterogeneous sources.
+ Collaborate closely with cross-functional teams across gRED to solve complex problems including developing models to predict antigen-antibody affinity, antibody-antigen complex structure, and developability properties.
+ Closely collaborate with drug discovery teams to contribute to the Roche large molecule portfolio, solving unique and challenging protein design and engineering tasks.
+ Contribute to and drive publications and present scientific findings at internal/external venues.
**Who you are**
+ PhD degree in Computational Biology, Structural Biology, Computer Science, Physics or related disciplines, or a MS degree in the above disciplines with 3+years of industry research experience.
+ Demonstrated experience with Python and deep learning libraries such as Pytorch and/or TensorFlow and/or JAX.
+ Demonstrated research experience, including at least one first author publication or equivalent.
+ Publication record and experience contributing to research communities, including conferences like NeurIPS, ICML, ICLR, CVPR, ACL, etc.
+ Strong communication and collaboration skills.
**Additional desired qualifications:**
+ Experience working with data from biology, immunology or related disciplines.
+ Experience with antibody structure, function, and sequence data.
+ Public portfolio of computational projects (available on e.g. GitHub).
Relocation benefits are available for this job posting.
The expected salary range for this position based on the primary location of California is $147,600, - $274,000. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
**Benefits ( is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants ( .

**The Position**
We advance science so that we all have more time with the people we love. A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Roche.
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche's Research and Early Development organizations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximizing these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
Within the CoE organization, the Data and Digital Catalyst (DDC) organization drives the modernization of our computational and data ecosystems and integration of digital technologies across Research and Early Development to enable our stakeholders, power data-driven science and accelerate decision-making.
The Engineering - AI Enablement group within DDC is accountable for. enabling AI! We do this across the board with our scientific and computational partners based on their goals. We help embed our AI strategy across our research organizations by providing employees with the tools and support needed to adopt AI into our daily work-helping us work smarter and enhancing our day-to-day work. We also build and deploy AI based solutions that reshape and transform business processes in order to unlock value at scale and optimise workflows. We also work on scaling up model training and inference, evaluating the quality of AI/ML models and output, and building impactful applications which accelerate the scientists doing the critical work of drug discovery and development. Partnering with colleagues to build, deploy and evolve a modern tech stack and utilities to enable our AI/ML and agentic efforts will be a key foundation to our success. Our aim is for everyone who can benefit from AI/ML to be able to leverage that utility where and when they need it, from data analysis to literature search to documentation writing. We are aiming for AI/ML to be an everyday utility. The team is cross-functional, impact driven, independent, and constantly evolving to meet the scientific needs.
**The Opportunity:**
As a machine learning engineer in AI Enablement, you will be working closely with folks that span the gamut from Computational Scientists, Research Scientists, AI/ML experts, Product leaders, DevOps, and everyone in between. You'll build, own, and constantly improve scalable AI/ML based systems that unlock the potential of our diverse scientific data, accelerating the discovery and development of life-changing treatments for patients.
+ Design, develop, and test robust, scalable, and maintainable AI/ML facing scientific web applications and backend systems.
+ Build tools to evaluate AI/ML model performance and establish new ways to understand AI quality.
+ Partner with product managers and scientists to understand user needs, shape requirements, and translate them into actionable technical specifications.
+ Develop and maintain systems for collecting, structuring, and storing diverse scientific data that support advanced analytics, machine learning, and other data-driven initiatives.
+ Implement, adopt, or evaluate new AI/ML algorithms and analytical techniques
+ Contribute to architectural decisions, code reviews, and the evolution of our development processes.
+ Be willing to span the stack and contribute where needed, even outside of your core area of expertise.
+ Stay up-to-date with emerging technologies and industry best practices and adopt a culture of continuous learning, collaboration, and curiosity.
**Who You Are:**
+ Master's or Ph.D. in Computer Science or similar technical field and 6+ years of professional experience in machine learning engineering roles (Principal Machine Learning Engineer); 12+ years (Senior Principal Machine Learning Engineer).
+ Strong proficiency with AI/ML frameworks, libraries, and toolsets.
+ Expert knowledge of statistics, machine learning theory, and algorithms.
+ Strong knowledge of ML performance optimization, GPU best practices.
+ Experience with kubernetes, relational databases, NoSQL databases, or data lakes, and experience working on cloud-native architectures in public clouds (ideally AWS).
+ Proven understanding and application of engineering best practices.
+ Excellent communication skills and ability to build trusted partnerships with internal and external collaborators.
+ Ability to quickly acquire new technologies and programming languages and a passion for continuous learning.
**Preferred But Not Required:**
+ Experience with imaging or biological data and processes is a strong plus.
+ Experience working with scientists or in a research environment is advantageous.
+ Experience with workflow automation, GenAI, and/or agents is a plus.
This position requires onsite work 3 days per week.
The expected salary range for this position based on the primary location of California is $176,400.00-$27,600.00 (Princial MLE) and 199,700-370,900 (Senior Principal MLE). Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits ( benefits are available for this posting.
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants ( .

**Summary:**
The Reality Labs team at Meta is looking for Computer Vision Researchers to support our Spatial AI team as we build towards our goal to transform the way people come together to interact, work and play.We explore, develop and deliver cutting-edge technologies that serve as the foundations for the current and future Reality Labs products including VR, AR, smart-glasses, AI agents, and robotics. We are committed to driving the state-of-the-art forward through innovation across ML perception in 2D and 3D, for both primitives (e.g. depth, segmentation, and semantic keypoints) as well as high-level (e.g. shape inference, 3D reconstruction, context/semantic understanding). The ideal candidate will help us develop the next generation of spatial and contextualized AI, and lay the foundations for a new computing paradigm that is built from the ground up to understand the physical world from egocentric devices. We are looking for experts in areas such as vision-language models, agentic AI, learning from demonstration, and representation learning.The potential to change the world is immense -- and we're just getting started. We encourage you to apply and join us!
**Required Skills:**
Computer Vision/Machine Learning Research Scientist (Spatial AI) Responsibilities:
1. Design and development of novel machine learning algorithms to solve problems in areas such as: vision-language models, agentic AI for multimodal systems, foundation models, 3D reconstruction with deep learning methods, depth estimation, semantic segmentation, 2D and 3D semantic key point detection, and object tracking
2. Define, build, and benchmark new capabilities needed for the next generation of AI
3. Communicate cross-functionally
4. Drive the team's goals and technical direction to pursue technical opportunities
5. Lead and collaborate with multidisciplinary engineering and research teams to develop technologies from early exploration and incubation to production
**Minimum Qualifications:**
Minimum Qualifications:
6. PhD degree in the field of Artificial Intelligence, Robotics, Computer Vision, Machine Learning, Natural Language Understanding, or equivalent practical experience
7. Significant industry experience in relevant areas
8. Leadership experience driving high-risk, high reward projects scientifically, including managing a team of research scientists and communicating to leadership
9. Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at conferences such as CVPR, ICCV, NeurIPS, or similar
10. Experience handling concurrent projects where timelines may be ambiguous or changing, and prioritizing by balancing required effort with resulting impact
11. Experience in Python
**Preferred Qualifications:**
Preferred Qualifications:
12. Experience with distributed systems or on-device algorithm development
13. Experience communicating research for public audiences of peers
14. Experience working and communicating cross-functionally in a team environment
15. Significant industry experience in relevant robotics related research areas, preferably large multimodal models, agentic AI, 3D reconstruction with deep learning methods
16. Leadership and interpersonal communication experience in working across many disciplines, driving best practices, and mentorship
17. Experience with deep learning frameworks (such as pytorch, tensorflow) and Python
18. Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward
**Industry:** Internet

As a Member of Technical Staff - Machine Learning, AI Safety, you will develop and implement cutting-edge safety methodologies and mitigations for products that are served to millions of users through Copilot every day. Users turn to Copilot for support in all types of endeavors, making it critical that we ensure our AI systems behave safely and align with organizational values. You may be responsible for developing new methods to evaluate LLMs, experimenting with data collection techniques, implementing safety orchestration methods and mitigations, and training content classifiers to support the Copilot experience. We're looking for outstanding individuals with experience in machine learning or machine learning infrastructure who are also strong communicators and great teammates. The right candidate takes the initiative and enjoys building world-class, trustworthy AI experiences and products in a fast-paced environment.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
**Responsibilities**
**Responsibilities**
+ Leverage expertise to uncover potential risks and develop novel mitigation strategies, including data mining, prompt engineering, LLM evaluation, and classifier training.
+ Create and implement comprehensive evaluation frameworks and red-teaming methodologies to assess model safety across diverse scenarios, edge cases, and potential failure modes.
+ Build automated safety testing systems, generalize safety solutions into repeatable frameworks, and write efficient code for safety model pipelines and intervention systems.
+ Maintain a user-oriented perspective by understanding safety needs from user perspectives, validating safety approaches through user research, and serving as a trusted advisor on AI safety matters
+ Track advances in AI safety research, identify relevant state-of-the-art techniques, and adapt safety algorithms to drive innovation in production systems serving millions of users.
+ Embody our culture and values.
**Qualifications**
**Qualifications**
**Required Qualifications**
+ Bachelor's Degree in Computer Science, or related technical discipline AND technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
+ OR equivalent experience.
+ Experience prompting and working with large language models.
+ Experience writing production-quality Python code.
**Preferred Qualifications**
+ Demonstrated interest in Responsible AI.
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