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Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI

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London
1 week ago
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Responsibilities

: Leading solution workshops to design scalable ML systems on AWS using services like VPC, IAM, SageMaker Studio, Lambda, and EKS You'll build CI/CD pipelines using GitHub Actions, Jenkins, and AWS CodePipeline for deploying traditional ML, GenAI models, and AI agents Deploying LLMs (, via Huggingface) and construct AI agent workflows using tools like LangChain, LangGraph, and custom orchestrators Your expertise will help reduce cloud costs with GPU acceleration, auto-scaling, and spot instances To implement model lifecycle tools (MLflow, SageMaker Registry), performance dashboards, alerts, and automated retraining pipelines Connecting ML models to client systems using APIs, Kafka, and build agent workflows with vector databases (Pinecone, Weaviate) You'll enforce secure,pliant, and ethical practices-VPC design, IAM policies, data encryption, and adherence to GDPR You'll be a trusted advisor and mentor, presenting technical solutions, managing expectations, and guiding junior team membersAbout the candidates:University degree inputer Science, Mathematics or in a directly related field ( min grade) 3+ years in MLOps/ML Engineering experience, plus 5+ years in Python software development or data science Skilled in SageMaker (training, endpoints, pipelines), Lambda, Step Functions, S3, and CloudWatch Proficiency with Terraform or AWS CDK, Docker, and Kubernetes (EKS/Fargate) Experienced with MLflow (or alternatives), GitHub Actions, Jenkins, AWS CodePipeline, and automated testing You've got hands-on experience with deploying LLMs and building AI agents using LangChain or custom frameworks Strong background in building data pipelines with Airflow/dbt and managing features via Feast or similar tools You have experience building dashboards with CloudWatch/Prometheus/Grafana and implementing data validation with Great Expectations It would be beneficial to have exposure to consulting/presales, MCP deployment, Databricks, and AWS ML Specialty certified Reply is an Equal Opportunities Employer andmitted to embracing diversity in the workplace. We provide equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type regardless of age, sexual orientation, gender, identity, pregnancy, religion, nationality, ethnic origin, disability, medical history, skin colour, marital status or parental status or any other characteristic protected by the Law.

Reply ismitted to making sure that our selection methods are fair to everyone. To help you during the recruitment process, please let us know of any Reasonable Adjustments you may need.

Job ID 10760

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