Job Description

Description

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.


Headquartered in Bristol (UK), we combine modern engineering methods with cutting-edge commercial technology to create adaptable, mission-critical systems. We focus on solving the tough challenges that others overlook, ensuring our customers can operate effectively in an ever-changing world.

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 get useful AI into the hands of users. Our ML team works end-to-end, from R&D to deployment, across traditional ML, deep learning, data engineering, and LLM and agentic systems.

As a Lead ML Engineer, you will be responsible for technical leadership and development effort on projects and products. You will design end-to-end solutions from early concepts to deployment, owning the quality of the software and ML solution. As a lead you will be expected to manage junior ML Engineers and mentor colleagues in the team, uphold coding standards and act as a trusted point of expertise for good ML, data, and software practices and advocate for this around the business.


No prior defence experience is required. We're interested in people who've built and deployed AI systems in demanding environments and are passionate about delivering tangible value to end users, whatever the sector.

Key areas of responsibility

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. You are a multiplier for the team's capability.

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.

Key skills, experience and behaviours

Essential:

Proven delivery:

experience leading technical work that delivered measurable impact in production, especially on edge, embedded, or mission-critical systems. You've made decisions that mattered and lived with the outcomes.

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.

Beneficial knowledge:

General tooling and platforms:

Databricks, AWS, GitHub, 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.

About you

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.

Location and clearance

This role is based in Bristol and requires working from the office three days per week, with occasional travel to customer site(s) in London.




Further information on UK security clearance levels is available here:


https://www.gov.uk/government/publications/united-kingdom-security-vetting-clearance-levels

Working at Rowden

We are committed to building a flexible, inclusive, and enabling company. Our aim is to create a diverse team of talented people with unique skills, experience, and backgrounds, so please apply and come as you are!

We also recognise the importance of flexible working and support this wherever we can. We welcome the opportunity to discuss flexibility, part-time working requirements and/or workplace adjustments with all our applicants.

Rowden is a Disability Confident Committed company, and we actively encourage people with disabilities and health conditions to apply for our roles. Please let us know your requirements early on so that we can make sure you have everything you need up front to help make the recruitment process and experience as easy as possible.

Finally, if you feel that you don't meet all the criteria included above but have transferable skills and relevant experience, we'd still love to hear from you!

About Rowden

What matters to us?

Our focus is on the end user. We exist to deliver the best possible outcomes for the users of our systems. Pace matters. The problems we solve are urgent. Our diverse skills and backgrounds make us better. Our team prides itself on being inclusive and multidisciplinary. We are radically honest. Saying what we mean, even when it isn't easy. We are pragmatists. We provide realistic, focused solutions that get to the point. * We improve continuously. We are relentless in our drive to make things better.