Machine Learning Engineer
Understanding Recruitment · Stevenage, England ·
60,000 - 70,000HertfordshireMachine Learning EngineerIf you're an ML Engineer who enjoys shipping and running AI systems in production more than spending your days experimenting with models, this could be a very good fit.
What's in it for you? Work on AI and LLM systems that are genuinely running in productionOwn problems across development, infrastructure and deployment, rather than being boxed into one areaBuild with modern GenAI technologies including RAG, agentic AI and LLMsSignificant exposure to AWS architecture, MLOps, CI/CD and observabilityFreedom to improve how AI services are deployed, monitored and scaledOpportunity to take increasing technical ownership and potentially step into a Senior/Lead roleRemote working with the option to spend time in the officeWhat you'll be working onBuilding and operating production AI/LLM servicesDesigning and scaling cloud infrastructure in AWSImproving CI/CD, infrastructure-as-code and automated deploymentsDeveloping and debugging Python services using tools such as FastAPI and PydanticBuilding production RAG pipelines, including embeddings, indexing, retrieval and rerankingImplementing monitoring, tracing and observability across AI servicesImproving system reliability, performance, compute efficiency and costOwning technical problems from development and staging through to productionWhat we're looking forYou'll ideally have 4+ years of relevant engineering experience, although depth of experience matters more than an exact number.
The strongest fit will be someone with: A background in ML Engineering, MLOps, Platform Engineering or Software EngineeringStrong Python development experienceHands-on experience building and operating systems in AWSExperience deploying and maintaining production ML or AI servicesGood understanding of CI/CD, containers and infrastructure-as-codeExperience with monitoring and observability tools such as Grafana, CloudWatch, Langfuse or similarSome practical exposure to LLMs, RAG, NLP or generative AIThe confidence to take ownership of production systems and help guide other engineers