MLOps Engineer

We are urgently seeking a highly skilled Senior MLOps Engineer with strong Data Science experience for a key role with a leading global technology consultancy at their London office. This is a fantastic opportunity to bridge the gap between cutting-edge AI/ML research and scalable, production-ready solutions. In this role, you will be the crucial link between Data Science and DevOps teams, focusing on deploying, managing, and automating the full machine learning lifecycle using a modern AWS stack.

Key Responsibilities:

• Act as the technical liaison between Data Science and DevOps, ensuring smooth deployment and integration of AI/ML models.
• Design, develop, and deploy microservices and standalone applications to serve models, including those from Hugging Face.
• Build, train, and evaluate ML models using AWS SageMaker, Bedrock, Glue, and Fargate.
• Manage the end-to-end ML lifecycle: from training and validation to versioning, deployment, monitoring, and governance.
• Develop and expose secure APIs using frameworks like Flask or FastAPI.
• Build and maintain automation pipelines and CI/CD integrations for ML projects using tools like Jenkins and Git.

Essential Skills & Experience:

• Proven experience as an MLOps Engineer with a solid background in Data Science and DevOps principles.
• Demonstrable hands-on experience deploying and maintaining AI/ML models in production using AWS SageMaker.
• Proficiency with AWS services: SageMaker, Bedrock, Glue, Kendra, ECS Fargate, and Lambda.
• Strong programming skills in Python and experience developing microservices and REST APIs (Flask/FastAPI).
• Proficiency with SQL, Git, and Jupyter/RStudio environments.
• Excellent soft skills with the ability to collaborate cross-functionally and explain complex technical concepts to non-technical stakeholders.

Work Arrangement: This is a hybrid role, requiring you to be onsite at the client's office in Stratford, London, 2 days per week (40%).

Ideal Candidate Profile: You are a Sr. Associate or Manager-level professional with hands-on experience in software delivery and client-facing environments. You are a proactive problem-solver, able to manage multiple priorities in a challenging, fast-paced setting. SC Clearance is preferable, but candidates with a minimum of 2 years' UK working experience will be considered. This is an urgent requirement, and we have a 15-day closing timeline for applications. If you are a collaborative technologist passionate about operationalizing machine learning, we would love to hear from you.