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. #Hiring #MLOps #MachineLearning #DataScience #AWS #SageMaker #DevOps #LondonJobs #TechJobs #HybridWorking #UrgentHire