Lead Machine Learning Engineer

Join to apply for the Lead Machine Learning Engineer role at Rowden
.

Department:
Engineering

Location:

Bristol, UK

We’re building the UK's next generation engineering powerhouse, providing critical technology that strengthens national security and resilience. At Rowden, we design and integrate advanced systems and products that sense, connect, and protect data in challenging environments where quick decisions are vital. Our solutions use intelligent automation to enhance speed and efficiency and are built to be reliable and straightforward for critical operations in remote or high‑pressure settings.

We are growing our ML team to support new projects and product development. We are looking for AI builders who will work on developing and deploying AI systems to solve complex problems with real‑world impact. You will join an existing ML team that works in close collaboration with software, hardware, and systems teams to bring useful AI to users. The team works end‑to‑end, from R&D to deployment, across traditional ML, deep learning, data engineering, and LLM‑ and agentic systems.

• Own and ship ML in production
  : take ideas from R&D to robust, maintainable deployments – often onto edge or embedded hardware.
• End‑to‑end ownership
  : lead the full lifecycle, data collection/curation, feature engineering, model training, evaluation, deployment, monitoring, and iteration.
• Technical leadership
  : set direction, guide design/architecture, perform reviews, mentor teammates, and raise the engineering bar.
• MLOps/LLMOps
  : CI/CD for models, containerisation/orchestration, experiment tracking and registry, model evaluation pipelines, safety guardrails, canaries, and performance monitoring.
• Cross‑team collaboration
  : partner with software, systems, and product colleagues; simplify complex topics for other disciplines and customers; champion AI and data.
• Data foundations
  : establish pragmatic data pipelines (batch/stream) that make curation, provenance, and reproducibility first‑class.

Essential

• Proven delivery
  : experience leading technical work that delivered measurable impact in production, especially on edge, embedded, or mission‑critical systems.
• Deep domain expertise
  : mastery in at least one major area of ML (e.g. optimisation, computer vision, sequence modelling, LLMs, probabilistic methods), with the ability to apply that depth to real production constraints.
• ML & maths depth
  : strong grounding in ML/DL (optimisation, generalisation, probability, model architecture) and the ability to reason about these trade‑offs in production.
• Software development
  : excellent Python skills; experience with low‑level languages like Rust is desirable.
• Interpersonal skills
  : strong communicator who can mentor, influence, and bridge technical and non‑technical audiences.
• Education
  : MSc or equivalent experience required.
• Builder mindset
  : bias to action, ownership over outcomes, and comfort working through ambiguity.

Desirable

• LLMs & agentic systems
  : practical experience with prompt optimisation, retrieval/RAG, evaluation, and tool orchestration; aware of latency, cost, and reliability trade‑offs.
• MLOps excellence
  : reproducible pipelines, model versioning, CI/CD, observability, and automated evaluation.
• Data engineering
  : proficiency with Databricks, Apache Spark, Delta Lake, MLflow, and SQL; experience integrating datasets and maintaining data quality.
• Education
  :
  PhD in AI/ML/CS or related field.

• General tooling and platforms:
  Databricks, AWS, Git Hub, Docker/Kubernetes, MLflow, Jira.
• Edge deployments:
  Nvidia Jetson (e.g. AGX Orin), Raspberry Pi, or other embedded accelerators.
• LLM/Agent tooling: DSPy, llama.cpp, vLLM, evaluation harnesses, prompt optimisation, agent frameworks.
• Operational practices: incident response, canary deployments, cost/performance optimisation across edge and cloud.

You’ve built ML systems that persist – deployed in real settings, iterated over time, and improved through real‑world feedback. You enjoy guiding others, keeping systems healthy, and making the complex understandable.

This role is based in Bristol and requires…