18 Jobs für Data Science in Schweiz

Bring more to life.
Are you ready to accelerate your potential and make a real difference within life sciences, diagnostics and biotechnology?
At Genedata, one of Danaher's ( 15+ operating companies, our work saves lives - and we're all united by a shared commitment to innovate for tangible impact.
You'll thrive in a culture of belonging where you and your unique viewpoint matter. And by harnessing Danaher's system of continuous improvement, you help turn ideas into impact - innovating at the speed of life.
The biopharmaceutical industry is undergoing a digitalization revolution, adopting data-driven R&D approaches to develop innovative therapies quicker. Genedata's market-leading enterprise software is fueling this revolution, enabling leading biopharma, biotech, and CRDMO companies worldwide to automate processes and leverage biopharma R&D data analytics so they can find breakthrough therapies faster. Join this digital transformation and help scientists around the world accelerate the pace of biopharma R&D.
Learn about the Danaher Business System ( which makes everything possible.
The Data Science Consultant - Precision Medicine you will be a key member of our dynamic team, empowered to have a significant impact on the continuous growth of our business. You will work with our partners in biopharma across the entire drug R&D value chain, achieving their vision of precision medicine through leveraging the full power of clinical, phenotype, molecular, and imaging data. This includes using your scientific and technical knowledge to solve real-world scientific challenges.
This position reports to the head of Customer Success Team and is part of Genedata Profiler, located in Basel.
In this role, you will have the opportunity to:
+ Play a key role in Genedata Profiler Implementation projects, as a scientific expert providing consulting, business process analysis, and solution design.
+ Scope and execute customer Data Science projects delivering results and presentations that meet the high standards our clients expect.
+ Build and maintain strong relationships with customers, serving as their primary contact for scientific and technical matters.
+ Collaborate with Sales to identify new opportunities and contribute to business growth.
+ Share insights from customer interactions with internal teams including Sales, SW-Development, and Product Management.
The essential requirements of the job include :
+ PhD or MS in bioinformatics, data sciences, health sciences, or related discipline, with strong foundations in both computational and life sciences.
+ Excellent communication and presentation skills, with the ability to engage diverse audiences and simplify complex scientific concepts.
+ Proficiency in scripting languages such as Python or R, and extensive experience analyzing multi-omics, biomarker, imaging, and clinical data - ideally within biopharma research.
+ Strong project management abilities, with a track record of delivering high-quality within agreed timelines.
+ Exceptional interpersonal skills and the ability to collaborate effectively within interdisciplinary teams, both internally and externally.
Travel, Motor Vehicle Record & Physical/Environment Requirements :
+ Regular travel within Europe (approximately once or twice per month).
+ Occasional travel to the United States.
It would be a plus if you also possess previous experience in:
+ Experience with biopharma R&D processes.
+ Familiarity with interactive data visualization tools such as R Shiny or Python Dash.
+ Experience identifying and developing new business opportunities in collaboration with commercial teams.
Genedata, a Danaher operating company, offers a broad array of comprehensive, competitive benefit programs that add value to our lives. Whether it's a health care program or paid time off, our programs contribute to life beyond the job.
Join our winning team today. Together, we'll accelerate the real-life impact of tomorrow's science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life.
For more information, visit .

Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain
Develop machine learning models and computer vision algorithms for wood property analysis, sorting, and grading. Contribute to the TIMBERHAUS project by applying advanced image processing and AI methods for timber quality assessment. Integrate experimental data with computational models and collaborate closely with lab teams. Publish research findings, present at conferences, and support PhD students. Help shape new research proposals and assist in securing funding. Your profile

• PhD in Computer Science, Data Science, Machine Learning, or a related discipline. 
• Proven experience in computer vision (e.g. image processing, deep learning, object detection, segmentation) and machine learning techniques. 
• Programming skills in Python and relevant ML frameworks (TensorFlow, PyTorch), experience with version control systems (e.g., Git). 
• Strong publication record in reputable journals and conferences. 
• Interest in wood technology or biomaterials is a plus. 
• Excellent communication skills in English; proficiency in German is beneficial.

We offer a fully funded 1‑year position, with the possibility of extension, in an inspiring, multidisciplinary and international research environment at a leading Swiss institute. The successful candidate will have access to state-of-the-art infrastructure and opportunities for collaboration within the ETH Domain. Professional development, networking and participation in innovative projects are supported. We provide competitive salary and employment conditions in the Zurich region.

**Summary:**
Meta is seeking experienced engineers to join our teams in building cutting-edge products that connect billions of people around the world. As a member of our team, you will have the opportunity to work on complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for committed individuals who can help us advance the way people connect globally. If you're interested in joining an industry leading team of engineers and researchers to work on exciting projects that have significant impact, we encourage you to apply.
**Required Skills:**
Software Engineer, Machine Learning Responsibilities:
1. Collaborate with cross-functional teams (product, design, operations, infrastructure) to build creative application experiences
2. Implement custom user interfaces using latest programming techniques and technologies
3. Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews
4. Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members
5. Architect efficient and scalable systems that drive complex applications
6. Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt
7. Work on a variety of coding languages and technologies
8. Establish ownership of components, features, or systems with end-to-end understanding
**Minimum Qualifications:**
Minimum Qualifications:
9. Programming experience in a relevant language
10. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
11. Demonstrated experience driving change within an organization and leading complex technical projects
12. Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions
**Preferred Qualifications:**
Preferred Qualifications:
13. Masters degree or PhD in Computer Science or a related technical field
14. Background in machine learning, especially applied to ranking, recommendation systems, or large-scale predictive modeling
15. Experience in Reinforcement Learning, Causal Modeling or Sequence Modeling
16. Experience in shipping new products or landing product iterations at scale
17. Demonstrated experience with data structures and algorithms, including graph theory and optimization techniques
**Industry:** Internet

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.
**The Position**
The Large Molecule Drug Discovery group in Basel within Prescient Design/AI4DD, a division devoted to developing structural and machine learning-based methods for protein design within the new Computational Sciences Center of Excellence (CoE), seeks exceptional researchers who have a demonstrated research background in machine learning and protein structural biology and design, a passion for independent research and technical problem-solving, and a proven ability to develop and implement ideas from research.
We are looking for talented Senior ML Scientists to join Prescient Design/AI4DD. The successful candidate will contribute to our antibody design efforts, partner with biologists, technologists and drug discoverers to develop new machine learning methods for de novo protein design with special application to protein therapeutics.
**The Opportunity**
+ Develop cutting-edge machine learning methods for analyzing biological data, focusing on structural biology and chemical molecules.
+ Deliver deep learning-based software solutions that accelerate drug discovery, design, and therapeutic development.
+ Collaborate with talented AI/ML scientists and form close working relationships with teams across Roche's global research and early development organizations.
+ Publish high-quality, impactful scientific articles and present your findings at major conferences and internal meetings.
+ Write structured, tested, and maintainable code, participating in code reviews to ensure quality and distribute knowledge.
+ Actively shape and contribute to our collaborative and innovative team culture.
**Who You Are**
+ You hold a PhD in a quantitative field (such as Computer Science, Physics, Mathematics, or Statistics) and have a strong record of high-impact scientific publications.
+ You possess 3+ years of hands-on experience designing and training machine learning models on large and complex datasets, ideally with biochemical data.
+ You have demonstrated experience with modern machine learning techniques, including neural networks on graphs (e.g., graph convolution) or sequence models (e.g., self-attention).
+ You are highly fluent in Python and proficient with at least one deep learning framework (e.g., PyTorch, TensorFlow, JAX).
+ You are an excellent communicator and collaborator, fluent in both written and spoken English, with a passion for driving projects in a cross-functional environment.
**Who we are**
A healthier future drives us to innovate. Together, more than 100'000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.
Let's build a healthier future, together.
**Roche is an Equal Opportunity Employer.**

**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:**
+ Bachelor's or Master's in Computer Science or similar technical field and 2+ years of professional experience in machine learning or similar relevant experience
+ 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 South San Francisco, CA is $134,100-249,100 . 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:**
Meta is seeking talented principal engineers to join our teams in building cutting-edge products that connect billions of people around the world. As a member of our team, you will manage complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for passionate individuals who can help us advance the way people connect globally. If you're interested in leading a world-class team of engineers and researchers to work on exciting projects that have significant impact, we encourage you to apply.
**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. Lead long term technical strategy and roadmap for large cross-company efforts
7. Suggest, collect and synthesize requirements and create an effective feature roadmap
8. Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt
**Minimum Qualifications:**
Minimum Qualifications:
9. Programming experience in a relevant language
10. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
11. Proven track record of planning multi-year roadmap in which short-term projects ladder to the long-term mission
12. Experience driving large cross-functional/industry-wide engineering efforts
13. Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions
14. Experience communicating and working across functions to drive solutions
15. Experience mentoring/influencing experienced engineers across organizations
**Preferred Qualifications:**
Preferred Qualifications:
16. B.S. Computer Science or related technical field
17. Experience with Hadoop/HBase/Pig or MapReduce/Sawzall/Bigtable/Hive/Spark
18. Experience in shipping products to millions of customers or have started a new line of product
**Industry:** Internet

**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:**
+ Bachelor's or Master's in Computer Science or similar technical field and 4+ years of professional experience in machine learning engineering roles
+ 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 $147,500-273,900 . 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 ( .

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.