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Senior Machine Learning EngineerBAE Systems Digital IntelligenceLondon, England, United Kingdom
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Senior Machine Learning Engineer

BAE Systems Digital Intelligence
  • GB
    London, England, United Kingdom
  • GB
    London, England, United Kingdom
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About

Senior Machine Learning Engineer Location:
London, UK Full‑time
BAE Systems Digital Intelligence is a global cyber and intelligence firm with 4,500 experts across 10 countries. We collect, connect and understand complex data to provide digital advantage in the most demanding environments for governments, armed forces and commercial businesses.
We are hiring a Senior ML Engineer to design, develop and iterate machine learning models that underpin national security objectives. The role will involve collaboration with Data Scientists, Software Engineers, Product Management and Government stakeholders throughout the full life‑cycle from hypothesis through to production deployment, leveraging AWS‑based infrastructure and modern MLOps/LLMOps tooling.
Core Duties
Design and develop machine learning models for traditional ML use cases and GenAI/LLM applications.
Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements.
Transition validated experiments into production‑ready solutions, working closely with engineers on deployment and monitoring.
Build and optimise ML pipelines using AWS services and experiment tracking tools.
Develop and integrate LLM‑powered solutions for evaluation and production monitoring.
Implement robust experiment tracking, model versioning and reproducibility practices with full audit trails.
Design feature engineering approaches and contribute to feature store development.
Support production models through monitoring, performance analysis and continuous improvement.
Apply responsible AI practices, including model explainability and fairness assessment.
Present experiment findings and production outcomes to stakeholders, articulating operational and strategic value.
Mentor junior colleagues and share learnings across the team.
About You
Hands‑on experience developing and deploying ML models in Python (scikit‑learn, XGBoost, PyTorch, or TensorFlow).
Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments.
Proven skill in experiment design: hypothesis formulation, A/B testing methodology and statistical evaluation.
Track record transitioning models from experimentation to production with appropriate governance and quality controls.
Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control).
Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures.
Familiarity with LLMOps tooling such as LangSmith, LangChain or LangGraph.
Understanding of model evaluation, validation techniques and production monitoring.
Experience working in cross‑functional teams from problem framing through to production delivery.
Ability to communicate complex findings to non‑technical audiences clearly.
Strong problem‑solving skills and the judgment to recognise when AI is not the answer.
Preferred Experience
Advanced LLM techniques: agents, tool use, and agentic workflows.
Vector databases (Pinecone, Weaviate, pgvector) for RAG. Feature stores (Feast, AWS Feature Store).
Infrastructure‑as‑Code (Terraform, CloudFormation).
Large‑scale data processing frameworks (Spark, Dask).
Data governance and compliance frameworks.
Experience in regulated industries (finance, healthcare, or similar).
Security Clearance:
Required. Candidates must be eligible for, or alreadyfase, security clearance and willing to go through the required process.
How we will support you
Work‑life balance importance; core‑hour flexibility and part‑time options available.Minimum 3 days per week in the office to support client engagement.
25 days holiday per year, with option to buy/sell and carry over.
Private medical and dental insurance; competitive pension; cycle‑to‑work; taste cards and more.
Dedicated Career Manager to support career development.
Company bonus scheme participation.
Access to diversity and support groups across gender, mental health, etc.
About our team Our team is resourceful, innovative and dedicated. We work from a mix of disciplines, delivering high‑quality solutions across the public sector. Joining our National Security business means contributing to the most trusted partner for our national security clients, with a legacy of over 40 Kyiv years of experience.
Seniority level Mid‑Senior level
(cls.position.type) prêmio.
Job function Engineering and Information Technology
ойчив Division overview: Government We defend the connected world and ensure the protection of nation‑states, focusing on cyber defence and key infrastructure protection.
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  • London, England, United Kingdom

Languages

  • English
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