Overview Job ID: 2916032 | AWS EMEA SARL (UK Branch) - F93
Are you looking to work at the forefront of Machine Learning and AI? This role is with the AWS Industries Team at AWS, helping customers implement Generative AI solutions and realize transformational business opportunities in strategic industry verticals. The team consists of data scientists, engineers, and architects who work with customers to build bespoke generative AI solutions, imagine and scope high-value use cases, train and fine-tune models, and deploy applications at scale. The team provides guidance on applying generative AI responsibly and cost efficiently.
You will work directly with customers in a fast-paced environment, design and run experiments, research new algorithms, and explore ways to optimize risk, profitability, and customer experience. You will use GenAI and related techniques to design, evangelize, and implement cutting-edge solutions for complex problems.
Key job responsibilities
Collaborate with AI/ML scientists, engineers, and architects to research, design, and evaluate cutting-edge generative AI algorithms and build ML systems to address real-world challenges.
Interact with customers to understand business problems, assist in implementing generative AI solutions, deliver briefing and deep dive sessions, and guide adoption patterns and paths to production.
Create and deliver best-practice recommendations, tutorials, blog posts, publications, sample code, and presentations for technical, business, and executive stakeholders.
Provide customer and market feedback to Product and Engineering teams to help define product direction.
About the team
Diverse Experiences: Amazon values diverse experiences and encourages applicants even if all preferred qualifications are not met.
Why AWS
AWS is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and continue to innovate, trusted by startups to Global 500 companies.
Work/Life Balance
We value work-life harmony and strive for flexibility as part of our working culture, supporting you at work and at home.
Inclusive Team Culture
We foster a culture of inclusion with employee-led affinity groups and ongoing learning experiences to embrace our differences.
Mentorship and Career Growth
We support knowledge sharing, mentorship, and resources to help you develop professionally.
BASIC QUALIFICATIONS
2+ years of data science experience and 3+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab).
3+ years of experience with machine learning/statistical modeling, data analysis tools and techniques, and knowledge of performance-affecting parameters.
Experience applying theoretical models in an applied environment.
Bachelor’s degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.
PREFERRED QUALIFICATIONS
PhD in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.
5+ years of experience with machine learning/statistical modeling tools and techniques.
Hands-on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer).
Experience training and fine-tuning large language models (LLMs) and knowledge of AWS platform and tools.
Amazon is an equal opportunities employer. We believe that a diverse workforce is central to success. Recruiting decisions are based on experience and skills. We value your passion to discover, invent, simplify and build. Please consult our Privacy Notice to understand how we collect, use, and transfer personal data of candidates.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you require a workplace accommodation during the application or hiring process, including support for interview or onboarding, please visit our accommodations page for more information.
Location: ES, Community of Madrid, Madrid
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