Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineer

Rowden
Bristol
2 weeks ago
Create job alert
Machine Learning Engineer – Rowden

Location: Bristol, UK


Compensation: £40,000 – £55,000 per year


Rowden is building the UK’s next‑generation engineering powerhouse, delivering critical technology that strengthens national security and resilience. Our solutions use intelligent automation to enhance speed and efficiency and are built for reliability in remote or high‑pressure settings.


Overview

We are growing our ML team to support new projects and product developments. As an ML Engineer you will work on developing and deploying AI systems to solve complex problems with real‑world impact. You’ll join an existing team that collaborates closely with software, hardware and systems colleagues to bring useful AI into the hands of users. The team works end‑to‑end – from R&D to deployment – across traditional ML, deep learning, data engineering, and LLM/agentic systems.


Key Responsibilities

  • Build and ship models and services from prototyping to production, writing maintainable code, tests, and documentation.
  • Experiment with data collection, feature engineering, model training and evaluation, and iterate with measurable outcomes.
  • Implement MLOps practices: training/serving pipelines, experiment tracking, CI/CD for ML, and basic observability.
  • Collaborate widely with software, systems and product teams to deliver features effectively.
  • Share knowledge through pair programming, code reviews, and by contributing to a positive, pragmatic engineering culture.

Key Skills, Experience & Behaviours

  • Applied ML experience: typically 1–5 years developing and delivering ML systems.
  • ML fundamentals: solid grounding in core ML/DL methods and the mathematics that underpin them; ability to reason about failure modes and trade‑offs.
  • LLMs & agentic systems: some hands‑on experience (e.g., RAG, evaluation, prompt tooling) and eagerness to deepen expertise.
  • MLOps foundations: containerisation, reproducible training, experiment tracking, model packaging/serving, basic observability.
  • Data engineering: experience with Databricks, Apache Spark, Delta Lake, MLflow, Unity Catalog, and Databricks SQL/Workflows.
  • Software development: strong Python skills; experience with low‑level languages such as Rust is desirable.
  • Product mindset & communication: care about user outcomes and can explain decisions clearly to non‑ML teammates.
  • Builder, not just theorist: enjoy turning ideas into running systems and iterating with feedback.

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.

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 support flexible, hybrid working – average three days in the office per week – and welcome discussions about flexibility, part‑time work or workplace adjustments.


Rowden is a Disability Confident and Committed company and actively encourages people with disabilities and health conditions to apply. Please let us know your requirements early on so we can make the recruitment process and experience as easy as possible.


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


Job Details

  • Seniority level: Entry level
  • Employment type: Full‑time
  • Job function: Engineering and Information Technology
  • Industries: Technology, Information and Internet


#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer (Databricks)

Machine Learning Engineer (Databricks)

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.