Machine Learning Engineer, Generative AI Innovation Center

Amazon; London; On-site; GBP 60,000 - 100,000; Full time

Job summary

Join a forward-thinking company as a Machine Learning Engineer in a dynamic Generative AI Innovation Center. This role offers the chance to work on cutting-edge projects that leverage advanced machine learning models to solve real-world problems. Collaborate with diverse teams to design, implement, and optimize innovative ML solutions that enhance customer experiences and service performance. With a commitment to mentorship and career growth, this position provides an exciting opportunity to contribute to transformative technologies in a supportive and inclusive environment. If you are passionate about the intersection of software development and generative AI, this is the perfect role for you.

Benefits

Flexible working hours

Mentorship programs

Employee-led affinity groups

Diversity conferences

Work-life balance initiatives

Qualifications

• 8+ years of software development experience with a focus on ML.
• Experience in leading design and architecture of systems.

Responsibilities

• Solve complex technical problems across the stack.
• Design and maintain innovative ML solutions for service performance.

Skills

Software Development

Machine Learning

Data Analysis

Python

SQL

Mentoring

Education

Bachelor's degree in Computer Science

Tools

Machine Learning Frameworks

Data Querying Tools

Job description

Machine Learning Engineer, Generative AI Innovation Center

Job ID: 2943066 | Amazon Web Services Singapore Private Limited

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.

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:

1. Solve complex technical problems, often ones not solved before, at every layer of the stack.
2. Design, implement, test, deploy and maintain innovative ML solutions to transform service performance, durability, cost, and security.
3. Build high-quality, highly available, always-on products.
4. 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:

1. Build high-impact ML solutions to deliver to our large customer base.
2. Participate in design discussions, code review, and communicate with internal and external stakeholders.
3. Work cross-functionally to help drive business solutions with your technical input.
4. Work in a startup-like development environment, where you’re always working on the most important stuff.

About the team
AWS values diverse experiences. Even if you do not meet all of the 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.

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 (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.

BASIC QUALIFICATIONS

- 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

PREFERRED QUALIFICATIONS

- 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

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.