Senior Machine Learning Engineer - Generative AI & MLOps (AWS)

"Please note, this role is not able to offer visa transfer or sponsorship now or in the future."

About the role

As a Senior Machine Learning Engineer you will make an impact by designing, building, and deploying scalable AI and machine learning solutions that drive business innovation and measurable outcomes. You will be a valued member of the AI & Data Engineering team and work collaboratively with architects, data engineers, product owners, business stakeholders, and cross-functional technology teams.

In this role, you will

Design, develop, and deploy machine learning and Generative AI solutions using AWS cloud-native services and modern MLOps practices.

Build and operationalize end-to-end MLOps pipelines for model training, validation, deployment, monitoring, and lifecycle management using Amazon SageMaker.

Develop Generative AI applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, embeddings, and prompt engineering techniques.

Implement scalable, secure, and resilient AI/ML platforms using Docker, Kubernetes/EKS, CI/CD pipelines, and Infrastructure as Code practices.

Partner with technical and business stakeholders to translate requirements into production-ready AI solutions while ensuring performance, reliability, governance, and cost optimization.

Work model

We strive to provide flexibility wherever possible. Based on this role’s business requirements, this position is remote.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you are engaged in, as well as business and client requirements.

What you need to have to be considered

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

6–10 years of software development experience, including at least 3 years in Machine Learning Engineering, AI Engineering, or MLOps.

Strong proficiency in Pyth...