ML Ops Engineer

Job Title: ML Ops / LLM Ops Engineer Location: Hybrid (potentially 1 day per week in east London) Contract: 6 month Contract Day Rate: £400 per day (Outside IR35) About the Role We are seeking an experienced ML Ops / LLM Ops Engineer to join a high-profile digital transformation initiative. This role focuses on operationalising advanced Machine Learning services including Transformers, Large Language Models (LLMs), Automatic Speech Recognition (ASR), and Text-to-Speech (TTS) solutions. You will work closely with developers, technical leads, product owners, and QA teams to design, deploy, and support production-grade ML services. This is a fast-moving environment where cutting-edge Generative AI technologies are constantly evolving, so adaptability and technical excellence are essential. Key Responsibilities • Design and implement tooling and technologies to support ML models and LLMs in production. • Deploy, maintain, and optimise machine learning services within a cloud environment (AWS). • Recommend and implement prompt management tools and provide expertise in prompt engineering. • Introduce and manage observability, monitoring, and evaluation frameworks for ML and AI services. • Enable auto-evaluation of prompts and models against domain-specific requirements. • Build Python-based microservices, data pipelines, and serverless functions. • Collaborate with stakeholders to translate data and AI requirements into scalable solutions. Essential Experience & Skills • 5+ years' engineering experience, with at least 3 years in ML Ops, Data Engineering, or AI infrastructure. • Strong Python engineering skills (Pandas, Numpy, Jupyter, FastAPI, SQLAlchemy). • Expertise in AWS services (certification desirable). • Proven experience deploying and supporting LLMs in production. • Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc.). • Experience with ML tooling (e.g. SageMaker, LangChain/LangSmith, MLflow, Dataiku, DataRobot). • Knowledge of embeddings, their applications, and limitations. • Hands-on experience in Agile / Lean / XP environments. • Excellent communication, problem-solving, and cross-team collaboration skills. • Proactive interest in Generative AI trends and best practices. Desired Skills • Experience with chatbots and conversational AI (voice or text). • Familiarity with Terraform, Helm, Kubernetes, or Postgres. • Exposure to Data Science, NLP, Explainable AI (XAI). • Real-world delivery of Generative AI solutions, especially LLM-driven applications. • Rates depend on experience and client requirements