Sr Machine Learning Engineer, Generative Ai ID-5210
8+ years of non-internship professional software development experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience building complex software systems that have been successfully delivered to customers
- Experience as a mentor, tech lead or leading an engineering team
- 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
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.
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Key job responsibilities
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. You’ll also:
- Solve complex technical problems, often ones not solved before, at every layer of the stack.
- 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.
A day in the life
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. You’ll also:
- Build high-impact ML solutions to deliver to our large customer base.
- Participate in design discussions, code review, and communicate with internal and external stakeholders.
- Work cross-functionally to help drive business solutions with your technical input.
- Work in a startup-like development environment, where you’re always working on the most important stuff.
About the team
Diverse Experiences
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.
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. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender 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. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Singapore, SGP
- 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
