Ingénieur En Apprentissage Automatique Senior | Senior Machine Learning Engineer, Professional Services

Machine Learning Engineer Opportunity At Amazon Web Services

Are you excited about building software solutions around large, complex Machine Learning (ML) and Deep Learning (DL) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Artificial Intelligence (AI)? Eager to learn from many different enterprises' use cases of AWS ML and DL? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades - pioneering and shaping the world's AI technology?

At Amazon Web Services (AWS), we're hiring technical Machine Learning Engineers to collaborate with our Data Scientists to deliver ground-breaking solutions for customers. We are looking for Engineers with Data Science experience and Data Scientists with Engineering experience to support our efforts in the Enterprise, IoT, and start-up communities. We want to take your full-stack Data Science know-how to a new level by empowering AWS customers to maximize the benefits they receive through AI/ML on the AWS platform. This means building and operationalizing ML and DL solutions for our customers while helping them adopt modern Machine Learning best practices throughout every stage of their model development lifecycle.

AWS Professional Services is a unique consulting team. We pride ourselves on being customer obsessed and highly focused on the ML enablement of our customers. If you have experience with ML, including building, deploying, and monitoring models, we'd like you to join our team. A familiarity with cloud solutions and DevOps best practices is key as you will work with teams of Data Scientists, Data Engineers, and Architects to build truly end-to-end solutions. You must be prepared and eager to learn new technologies in this role.

You will provide deep and broad insight to customers and partners to help remove constraints that prevent them from leveraging AWS services to create strategic value. A commitment to team work, hustle, and communication skills are important in this role. Creating reliable, scalable, and high-performance AI/ML solutions requires strong technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience building large-scale distributed systems.

Key Job Responsibilities

• Lead end-to-end machine learning projects, from understanding business needs to data preparation, model development, deployment, and monitoring.
• Design and implement data platforms that support high-performance, reliable, and secure data platforms.
• Design scalable ML solutions and operations (MLOps) using AWS services. Leverage Generative AI solutions when applicable.
• Build and evaluate predictive models to provide actionable insights for forecasting, resource optimization, and customer trends.
• Collaborate with cross-functional teams (DevOps, Data Engineering, IoT, HPC) to prepare, analyze, and operationalize data and models.
• Serve as a trusted advisor to customers on AI/ML solutions and cloud architectures.
• Coach and mentor junior individuals to support their professional growth.
• Develop technical content, such as white papers and blog posts, to share best practices.
• Ensure solutions meet industry standards and support customers in advancing their AI/ML and cloud adoption strategies.

This is a customer-facing role with potential travel to customer sites as needed.

About The Team

Diverse Experiences

Amazon values diverse experiences. Even if you do not meet all of the preferred 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.

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. 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 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.