Machine Learning Engineer

Leap29; Greater London; On-site; GBP 85,000 - 125,000; Full time

Job summary

Leap29 in London is seeking a hands‑on Machine Learning Engineer to design, build and ship production ML systems, including LLM and generative AI features. You will take models from prototype to production, collaborating with data scientists, product managers and software engineers.

You will design, train and deploy models, build scalable pipelines for training and inference, and ensure monitoring and MLOps best practices are in place across cloud platforms.

Qualifications

• 4+ years' experience as a Machine Learning Engineer or similar
• Strong Python skills and ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Experience deploying models to production on cloud platforms
• Solid MLOps understanding: Docker, orchestration, experiment tracking
• Good communication and collaboration with data scientists and engineers

Responsibilities

• Design, train, evaluate and deploy ML models including LLM-based solutions into production
• Build scalable data and ML pipelines for training, inference and monitoring
• Develop AI features such as retrieval-augmented generation (RAG), embeddings and fine-tuning
• Turn experimental notebooks into robust, production-grade code
• Monitor production models for drift, latency, cost and reliability
• Set up MLOps: CI/CD, experiment tracking, model versioning, automated testing
• Collaborate with product and engineering to translate business needs into technical solutions
• Keep up with AI developments and bring practical ideas to the team
• Contribute to responsible AI practices, including bias checks and data privacy

Skills

Python programming

Communication

Team collaboration

Problem solving

Education

Bachelor's degree in CS/ML or equivalent

Tools

Docker

Kubernetes

MLflow

Airflow

Cloud platforms (AWS/Azure/GCP)

Job description

I am looking for a Machine Learning Engineer with hands‑on AI experience to design, build and ship production ML systems, including large language model (LLM) and generative AI features. You will take models from prototype to production, working closely with data scientists, product managers and software engineers.

Key responsibilities

• Design, train, evaluate and deploy machine learning models, including LLM‑based and generative AI solutions, into production
• Build and maintain scalable data and ML pipelines for training, inference and monitoring
• Develop AI features such as retrieval‑augmented generation (RAG), fine‑tuned models, embeddings and agent‑style workflows
• Work with data scientists to turn experimental notebooks into robust, testable, production‑grade code
• Monitor model performance in production and manage drift, latency, cost and reliability
• Set up and improve MLOps practices: CI/CD, experiment tracking, model versioning and automated testing
• Collaborate with product and engineering teams to scope problems and translate business needs into technical solutions
• Keep up with developments in AI and machine learning, and bring practical ideas to the team
• Contribute to responsible AI practice, including model evaluation, bias checks and data privacy

Requirements

• 4+ years' experience as a Machine Learning Engineer, or in a similar applied ML or software engineering role
• Strong Python skills and experience with ML frameworks such as PyTorch, TensorFlow or scikit‑learn
• Practical experience building AI or generative AI applications: LLMs, prompt engineering, RAG, vector databases or fine‑tuning
• Experience deploying and running models in production on a cloud platform (AWS, Azure or GCP)
• Solid understanding of MLOps tooling, e.g. Docker, Kubernetes, MLflow, Airflow or similar
• Good software engineering fundamentals: version control, testing, code review and working in an agile team
• Experience with SQL and working with large datasets
• Strong communication skills, with the ability to explain technical ideas to non‑technical colleagues
• A degree in Computer Science, Machine Learning, Mathematics or a related field, or equivalent practical experience

Ready to build production AI in London?