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Machine Learning Engineer (All Levels)
Job Location:
Yearly Salary:
Posted:
22 August 2026 (9 hours ago)
Posted:
Application Deadline:
19 November 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Department:
Job Summary
Were building the UKs next generation engineering powerhouse providing critical technology that strengthens national security and resilience.
We specialise in turning advances in sensing AI and communications into operational capability for the edge where connectivity may be degraded or denied. Our work focuses on accelerating the deployment of technology improving decision-making for frontline teams and protecting people and critical assets in demanding environments.
Headquartered in Bristol Rowden employs around 200 people and operates over 20000 square feet of engineering and manufacturing facilities. We have a growing international footprint and are one of Europes fastest-growing engineering businesses.
About the role
We are growing our ML team and hiring across mid senior lead and principal levels. We are looking for AI builders; you will be working on developing and deploying AI systems to solve complex problems that have real-world impact. Youll 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 foundation models and LLM/agentic systems. We are now hiring across a broad range of ML skills including model training evaluation optimisation infrastructure and deployment.
As an ML Engineer at Rowden you will contribute to own or lead development effort on projects and products depending on your experience and level. You will work from applied research through to production developing and deploying AI systems that solve complex problems with real-world impact. Our work is broad spanning edge and embedded deployment model evaluation performance optimisation data pipelines large-scale training and ML infrastructure all focused on bringing useful AI capability to edge and embedded environments. We are building a team with complementary strengths.
No prior defence experience is required. Were interested in people whove built and deployed AI systems in demanding environments and are passionate about delivering tangible value to end users whatever the sector.
This role offers hybrid working with a minimum of 3 days per week on-site at our Bristol HQ.
Candidates must be eligible for SC clearance.
More information about security clearance is available here: we have advertised a salary band for senior level roles and above compensation is tailored to the scope of the role and the specific experience a candidate brings. For this role we encourage applicants from outside of the advertised salary band to apply. We will discuss compensation openly at the first stage of the process and can share an indicative range before either side invests significant time.
This role offers hybrid working with a minimum of 3 days per week on-site at our Bristol HQ.
Candidates must be eligible for SC clearance.
More information about security clearance is available here: we have advertised a salary band for senior level roles and above compensation is tailored to the scope of the role and the specific experience a candidate brings. For this role we encourage applicants from outside of the advertised salary band to apply. We will discuss compensation openly at the first stage of the process and can share an indicative range before either side invests significant time.
Key areas of responsibility
- Own and ship ML in production: take ideas from R&D to robust maintainable deploymentsoften onto edge or embedded hardware.
- Train and adapt models: work on model development fine-tuning evaluation and optimisation for real-world use cases.
- Work at scale where needed: run and improve training and inference workloads across GPUs including multi-GPU or multi-node environments to support models that can perform reliably in constrained settings.
- Improve performance: profile optimise and debug ML systems across model code data pipelines inference stacks and hardware constraints.
- Own evaluation quality: design evaluation pipelines benchmarks test sets and feedback loops that help us understand model behaviour before and after deployment.
- End-to-end ownership: data collection/curation feature engineering model training evaluation deployment monitoring and iteration.
- 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.
- Data foundations: establish pragmatic data pipelines (batch/stream) that make curation provenance and reproducibility first-class.
- Raise the bar: depending on level mentor others guide technical decisions and improve engineering standards across the team.
Key skills experience and behaviours
Essential
- Proven delivery: experience building training evaluating optimising or deploying ML systems for real-world use ideally in demanding environments.
- Deep domain expertise: Strong capability in at least one major area of ML such as optimisation computer vision sequence modelling LLMs probabilistic methods model evaluation or large-scale training.
- 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: Strong Python skills and good software engineering habits including version control testing code review debugging and maintainability.
- Interpersonal skills: strong communicator who can mentor influence and bridge technical and non-technical audiences.
- Education: Degree postgraduate study or equivalent practical experience in machine learning computer science engineering mathematics or a related technical field.
- Builder mindset: bias to action ownership over outcomes and comfort working through ambiguity.
Desirable
- 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.
- Model training and optimisation: experience with pre-training fine-tuning distributed training inference optimisation or adapting models for constrained environments.
- Education: PhD in AI/ML/CS or related field.
Beneficial knowledge
- General tooling and platforms: Databricks AWS GCP GitHub Docker/Kubernetes MLflow Jira.
- Edge deployments: Nvidia Jetson (e.g. AGX Orin) Raspberry Pi or other embedded accelerators.
- Distributed model training & infra: Pytorch DDP FDSP and TorchTitan Megatron Slurm Run:ai DeepSpeed Kubernetes cloud or on-prem GPU clusters.
About you
Youve built ML systems that persistdeployed in real settings iterated over time and improved through real-world feedback. You enjoy guiding others keeping systems healthy and making the complex understandable.
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 typically operate a flexible hybrid-working model with an average 3 days in the office each week (dependent on the role). 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 dont meet all the criteria included above but have transferable skills and relevant experience wed still love to hear from you!
Required Experience:
IC
About Company
Rowden designs and builds systems, infrastructure, and applications to deliver mission advantage to those working to protect the security of the UK and its allies. We are setting a new standard in government technology provision: hyper-efficient engineering, better customer relationsh ... View more
