Senior Machine Learning Engineer

eFinancialCareers; Greater London; On-site; GBP 68,000 - 83,000; Full time

Benefits offered by this job

Competitive salary

Annual bonus

Private healthcare

Enhanced pension

Generous annual leave

Benefits package

Hybrid work

Job summary

eFinancialCareers is seeking a Senior Machine Learning Engineer for a London hybrid role. Design, develop, and deploy production‑ready ML solutions for defence, government, and national security sectors, collaborating with Data Scientists and Software Engineers.

The role focuses on MLOps and LLMOps, using AWS to build scalable and secure AI systems, with opportunities for mentorship and technical leadership.

Qualifications

• Strong Python experience with production ML development.
• Experience with ML frameworks PyTorch, TensorFlow, Scikit-learn.
• Experience deploying ML solutions on AWS (SageMaker, Lambda, S3).
• Familiarity with MLOps tools such as MLflow, Weights & Biases, or Data Version Control (DVC).

Responsibilities

• Design, develop, and deploy ML models for forecasts, classification, and anomaly detection.
• Build Generative AI and LLM-powered applications.
• Lead experiments with hypotheses, evaluations, and production deployment.
• Develop robust ML pipelines using AWS services and MLOps tooling.
• Implement experiment tracking, model versioning, and monitoring.
• Build feature pipelines and contribute to feature store development.
• Monitor production models and drive continuous improvements.
• Apply Responsible AI principles including explainability and governance.
• Mentor junior engineers and contribute to technical leadership.

Skills

Python

ML & AI

Communication

AWS

Tools

PyTorch

TensorFlow

Scikit-learn

XGBoost

MLflow

Weights & Biases

Job description

££75,000 GBP

Hybrid WORKING

Location: Central London, Greater London - United Kingdom Type: Permanent

Senior Machine Learning Engineer

Location: London (Hybrid)

Salary: £75,000 + Bonus + Excellent Benefits

Are you passionate about applying Machine Learning and Generative AI to solve real‑world problems at scale?

We're working with a leading technology consultancy delivering cutting‑edge AI solutions within the UK National Security sector. They're looking for a Senior Machine Learning Engineer to design, develop, and deploy production‑ready machine learning solutions that make a genuine impact across defence, government, and national security.

Working alongside Data Scientists, Software Engineers, and AI specialists, you'll take projects from experimentation through to production, leveraging modern MLOps and LLMOps practices on AWS to build scalable, secure AI systems.

What You'll Be Doing

• Design, develop, and deploy machine learning models for traditional ML use cases, including forecasting, classification, and anomaly detection.
• Build and deliver Generative AI and LLM-powered applications using modern AI frameworks.
• Lead experimentation cycles, defining hypotheses, running evaluations, and iterating on models before production deployment.
• Develop robust ML pipelines using AWS services and MLOps tooling.
• Implement experiment tracking, model versioning, monitoring, and reproducibility best practices.
• Build feature engineering pipelines and contribute to feature store development.
• Monitor production models, optimise performance, and drive continuous improvements.
• Apply Responsible AI principles, including explainability, governance, and fairness.
• Mentor junior engineers and contribute to technical leadership across the team.

What We're Looking For

• Strong commercial experience developing machine learning solutions using Python.
• Experience with frameworks such as:
• PyTorch
• TensorFlow
• Scikit-learn
• XGBoost
• Experience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3.
• Strong understanding of MLOps tooling, including MLflow, Weights & Biases, or Data Version Control (DVC).
• Experience developing LLM or Generative AI applications, including RAG architectures and prompt engineering.
• Knowledge of LLMOps frameworks such as LangChain, LangGraph, or LangSmith.
• Experience taking ML models from experimentation into production environments.
• Strong communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders.

Desirable Experience

• AI agents and agentic workflows.
• Vector databases such as Pinecone, Weaviate, or pgvector.
• Feature stores including Feast or AWS Feature Store.
• Docker, Kubernetes, or Amazon ECS.
• Infrastructure as Code using Terraform or CloudFormation.
• Big data processing technologies such as Spark or Dask.
• Experience working within regulated or highly secure environments.

What's On Offer

• Work on meaningful AI programmes supporting critical national security missions.
• Exposure to cutting‑edge Machine Learning, LLM, and Generative AI technologies.
• Flexible hybrid working with a strong focus on work‑life balance.
• Dedicated career development, mentoring, and technical progression.
• Competitive salary, annual bonus, private healthcare, enhanced pension, generous annual leave, and a comprehensive benefits package.