ML Ops Engineer

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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 ( 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

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    Job Type:
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