Senior Delivery Consultant - Machine Learning (GenAI), ProServe EMEA
Job 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 responsibilitiesCollaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate generative AI algorithms and build ML systems to address real-world challengesInteract with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to productionCreate and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholderAbout the teamDiverse ExperiencesAmazon 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 AWSAmazon 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 BalanceWe 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 CultureHere 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 GrowthWe’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.
Locations
- Switzerland, ZH, Zurich, Zurich, ZH, Switzerland
Salary
Salary not disclosed
Estimated Salary Rangemedium confidence
140,000 - 200,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- PhD, or Master's degree and 3+ years of applied research experienceintermediate
- 5+ years of building machine learning models for business application experienceintermediate
- Experience with programming in Java, Python or related languageintermediate
- Experience with neural deep learning methods and machine learningintermediate
Required Qualifications
- PhD, or Master's degree and 3+ years of applied research experience (experience, 3 years)
- 5+ years of building machine learning models for business application experience (experience, 5 years)
- Experience with programming in Java, Python or related language (experience)
- Experience with neural deep learning methods and machine learning (experience)
Preferred Qualifications
- Experience with LLM pre-training, fine-tuning, and evaluations (experience)
- Familiarity with distributed training and acceleration method/implementation/library for LLMs or large-scale ML in general, e.g., DeepSpeed, Nemo-Megatron, PyTorch Lightning. (experience)
- science backgrounds demonstrated by degrees in fields such as: (degree in fields such as)
- Mathematics (experience)
- Statistics (experience)
- Physics (various specializations) (experience)
- Molecular Biology (experience)
- Neuroscience (experience)
- 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 (experience)
Responsibilities
- Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate generative AI algorithms and build ML systems to address real-world challenges
- Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production
- Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholder
- 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.
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Senior Delivery Consultant - Machine Learning (GenAI), ProServe EMEA
Job 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 responsibilitiesCollaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate generative AI algorithms and build ML systems to address real-world challengesInteract with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to productionCreate and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholderAbout the teamDiverse ExperiencesAmazon 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 AWSAmazon 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 BalanceWe 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 CultureHere 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 GrowthWe’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.
Locations
- Switzerland, ZH, Zurich, Zurich, ZH, Switzerland
Salary
Salary not disclosed
Estimated Salary Rangemedium confidence
140,000 - 200,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- PhD, or Master's degree and 3+ years of applied research experienceintermediate
- 5+ years of building machine learning models for business application experienceintermediate
- Experience with programming in Java, Python or related languageintermediate
- Experience with neural deep learning methods and machine learningintermediate
Required Qualifications
- PhD, or Master's degree and 3+ years of applied research experience (experience, 3 years)
- 5+ years of building machine learning models for business application experience (experience, 5 years)
- Experience with programming in Java, Python or related language (experience)
- Experience with neural deep learning methods and machine learning (experience)
Preferred Qualifications
- Experience with LLM pre-training, fine-tuning, and evaluations (experience)
- Familiarity with distributed training and acceleration method/implementation/library for LLMs or large-scale ML in general, e.g., DeepSpeed, Nemo-Megatron, PyTorch Lightning. (experience)
- science backgrounds demonstrated by degrees in fields such as: (degree in fields such as)
- Mathematics (experience)
- Statistics (experience)
- Physics (various specializations) (experience)
- Molecular Biology (experience)
- Neuroscience (experience)
- 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 (experience)
Responsibilities
- Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate generative AI algorithms and build ML systems to address real-world challenges
- Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production
- Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholder
- 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.