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- Tasks: Develop and deploy advanced ML models to solve real-world problems using Generative AI.
- Company: Join AWS, the leading cloud platform, fostering innovation and diversity.
- Benefits: Enjoy flexible work-life balance, mentorship opportunities, and a culture of inclusion.
- Why this job: Make a global impact by collaborating on cutting-edge projects in a fast-paced environment.
- Qualifications: Bachelor's degree in computer science and 5+ years of software development experience required.
- Other info: Amazon is committed to diversity and offers support for candidates with disabilities.
Machine Learning Engineer, Generative AI Innovation Center Machine Learning Engineer, Generative AI Innovation Center Get AI-powered advice on this job and more exclusive features. Amazon launched the Generative AI (GenAI) Innovation Center (GenAIIC) in Jun 2023 to help AWS customers accelerate enterprise innovation and success with Generative AI ( Customers such as Highspot, Lonely Planet, Ryanair, and Twilio are engaging with the GAI Innovation Center to explore developing generative solutions. Amazon launched the Generative AI (GenAI) Innovation Center (GenAIIC) in Jun 2023 to help AWS customers accelerate enterprise innovation and success with Generative AI ( Customers such as Highspot, Lonely Planet, Ryanair, and Twilio are engaging with the GAI Innovation Center to explore developing generative solutions. GenAIIC provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and in the cloud. As a Machine Learning Engineer in GenAIIC, you are proficient in developing and deploying advanced ML models and pipelines to solve diverse customer problems using Gen AI. You will be working alongside scientists with terabytes of text, images, and other types of data and develop Gen AI based solutions to solve real-world problems. You\’ll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. Our ML Engineers Collaborate Across Diverse Teams, Projects, And Environments To Have a Firsthand Impact On Our Global Customer Base. You’ll Bring a Passion For The Intersection Of Software Development With Generative AI And Machine Learning. Design, implement, test, deploy and maintain innovative ML solutions to transform service performance, durability, cost, and security. Build high-quality, highly available, always-on products. Research implementations that deliver the best possible experiences for customers. As You Design And Code Solutions To Help Our Team Drive Efficiencies In ML Architecture, You’ll Create Metrics, Implement Automation And Other Improvements, And Resolve The Root Cause Of Software Defects. Build high-impact ML solutions to deliver to our large customer base. Work cross-functionally to help drive business solutions with your technical input. AWS values diverse experiences. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. 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. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & 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. 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. 8+ years of non-internship professional software development experience ~Experience building complex software systems that have been successfully delivered to customers ~ 5+ years experience in data querying languages (e.g. SQL), scripting languages (e.g. Python) with exposure to machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience ~ Bachelor\’s degree in computer science or equivalent 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. 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 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. Company – AWS EMEA SARL (UK Branch) Employment type Full-time Industries IT Services and IT Consulting Referrals increase your chances of interviewing at Amazon Web Services (AWS) by 2x Sign in to set job alerts for “Machine Learning Engineer” roles. Machine Learning Scientists and Engineers: AI for Quantum Machine Learning Engineer – Search and Recommendation Graduate Software Engineer 2025 – RegTech Research Engineer, ML, AI & Computer Vision We’re unlocking community knowledge in a new way. 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ML Engineer Intern employer: Amazon Web Services (AWS)
Contact Detail:
Amazon Web Services (AWS) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer Intern
✨Tip Number 1
Familiarise yourself with the latest trends in Generative AI and machine learning. Follow industry leaders on social media, read relevant research papers, and engage in online forums to stay updated. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Build a portfolio showcasing your projects related to machine learning and Generative AI. Include any relevant code samples, experiments, or case studies that highlight your skills. A strong portfolio can set you apart from other candidates and provide tangible evidence of your capabilities.
✨Tip Number 3
Network with professionals in the field by attending meetups, webinars, or conferences focused on machine learning and AI. Engaging with others can lead to valuable connections and insights about job opportunities, including potential referrals at AWS.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and algorithm questions relevant to machine learning. Use platforms like LeetCode or HackerRank to sharpen your skills. Being well-prepared will boost your confidence and improve your chances of impressing the interviewers.
We think you need these skills to ace ML Engineer Intern
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, software development, and any specific projects related to generative AI. Use keywords from the job description to align your skills with what Amazon is looking for.
Craft a Compelling Cover Letter: In your cover letter, express your passion for generative AI and how your background makes you a great fit for the role. Mention specific projects or experiences that demonstrate your ability to develop and deploy ML models.
Showcase Your Technical Skills: Include a section in your application that details your proficiency in data querying languages like SQL and scripting languages such as Python. Highlight any experience you have with machine learning tools and techniques.
Prepare for Technical Questions: Anticipate technical questions related to machine learning algorithms and software development practices. Be ready to discuss your previous projects and the impact they had on customer experience or business solutions.
How to prepare for a job interview at Amazon Web Services (AWS)
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning models and algorithms. Highlight specific projects where you've implemented ML solutions, especially those that relate to generative AI. This will demonstrate your technical proficiency and relevance to the role.
✨Understand the Company’s Vision
Research Amazon's Generative AI Innovation Center and its impact on customers. Familiarise yourself with their recent projects and how they leverage generative AI. This knowledge will help you align your answers with the company's goals during the interview.
✨Prepare for Problem-Solving Questions
Expect to face scenario-based questions that assess your problem-solving abilities. Practice articulating your thought process when designing experiments or optimising ML models. This will showcase your analytical skills and ability to think critically under pressure.
✨Emphasise Collaboration and Communication
As the role involves working across diverse teams, highlight your experience in collaborative projects. Share examples of how you've effectively communicated complex technical concepts to non-technical stakeholders, demonstrating your ability to work well in a team environment.
