Machine Learning Engineer

The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Machine Learning Engineer to join our team at Amazon Web Services (AWS). 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? In this role, you”ll work directly with customers to design, evangelize, implement, and scale AI/ML solutions that meet their technical requirements and business objectives. You”ll be a key player in driving customer success through their AI transformation journey, providing deep expertise in machine learning, generative AI, and best practices throughout the project lifecycle.

As a Machine Learning Engineer within the AWS Professional Services organization, you will be proficient in architecting complex, scalable, and secure machine learning solutions tailored to meet the specific needs of each customer. You”ll help 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, and define paths to navigate technical or business challenges. Working closely with stakeholders, you”ll assess current data infrastructure, develop proof-of-concepts, and propose effective strategies for implementing AI and generative AI solutions at scale. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.

This position requires that the candidate selected must currently possess and maintain an active TS/SCI security clearance.

Key job responsibilities

• Designing and implementing complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, including selecting and fine-tuning appropriate models for specific use cases
• Developing and deploying machine learning models and generative AI applications that solve real-world business problems, conducting experiments and optimizing for performance at scale
• Collaborating with customer stakeholders to identify high-value AI/ML use cases, gather requirements, and propose effective strategies for implementing machine learning and generative AI solutions
• Providing technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently, troubleshooting throughout project delivery and ensuring adherence to best practices
• Acting as a trusted advisor to customers on the latest advancements in AI/ML, emerging technologies, and innovative approaches to leveraging diverse data sources for maximum business impact
• Sharing knowledge within the organization through mentoring, training, creating reusable AI/ML artifacts, and working with team members to prototype new technologies and evaluate technical feasibility

Algorithms, Amazon Web Services (AWS), Artificial Intelligence (AI), Best Practices, Cloud Computing, Consulting, Customer Experience, Customer Support/Service, Data Analysis, Emerging Technology, Enterprise Computing, Experiment Design, Feasibility Analysis, Identify Issues, Machine Learning, Maintain Compliance, Mentoring, Performance Tuning/Optimization, Problem Solving Skills, Professional Services, Profit & Loss, Project Lifecycle, Proof of Concept, Prototyping, Requirements Management, Risk, Startup, Team Player, Technical Analysis, Technical Leadership, Use Cases

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.

Amazon.com Inc At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1 At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day - to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

Company Size: 10,000 employees or more

Industry: Retail