National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior MLOps / Machine Learning Engineer: LLMs & Agentic AI

Reply
London
6 days ago
Create job alert

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

Related Jobs

View all jobs

Senior Staff Machine Learning Scientist, Operations

Senior Staff Machine Learning Scientist, Operations (Basé à London)

Senior Staff Machine Learning Scientist, Operations (Basé à London)

Senior Machine Learning Engineer to develop a POC for a LLM-powered internal chatbot for internal information using machine leaning packages for a healthcare client

Graduate Machine Learning Engineer (Basé à London)

Graduate Machine Learning Engineer

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Jobs Skills Radar 2026: Emerging Tools, Frameworks & Platforms to Learn Now

Machine learning is no longer confined to academic research—it's embedded in how UK companies detect fraud, recommend content, automate processes & forecast risk. But with model complexity rising and LLMs transforming workflows, employers are demanding new skills from machine learning professionals. Welcome to the Machine Learning Jobs Skills Radar 2026—your annual guide to the top languages, frameworks, platforms & tools shaping machine learning roles in the UK. Whether you're an aspiring ML engineer or a mid-career data scientist, this radar shows what to learn now to stay job-ready in 2026.

How to Find Hidden Machine Learning Jobs in the UK Using Professional Bodies like BCS, Turing Society & More

Machine learning (ML) continues to transform sectors across the UK—from fintech and retail to healthtech and autonomous systems. But while the demand for ML engineers, researchers, and applied scientists is growing, many of the best opportunities are never posted on traditional job boards. So, where do you find them? The answer lies in professional bodies, academic-industry networks, and tight-knit ML communities. In this guide, we’ll show you how to uncover hidden machine learning jobs in the UK by engaging with groups like the BCS (The Chartered Institute for IT), Turing Society, Alan Turing Institute, and others. We’ll explore how to use member directories, CPD events, SIGs (Special Interest Groups), and community projects to build connections, gain early access to job leads, and raise your professional profile in the ML ecosystem.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.