5V Tech
Principal Machine Learning Team Lead
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Principal Machine Learning Engineer / ML Team Lead
Location: Bristol (Hybrid – 3 days onsite per week)
Salary: Up to £120000
Employment: Permanent
Security Clearance: Must be eligible for UK DV clearance
The Opportunity
We're working with an innovative UK technology company that is expanding its Machine Learning capability and looking to appoint an experienced Principal Machine Learning Engineer / ML Team Lead.
This is an opportunity to work on technically challenging, real-world AI and ML projects, developing solutions that operate in demanding environments where reliability, performance, security, and computational constraints are critical.
The company is investing heavily in its ML capability and is looking for someone who can combine deep hands-on technical expertise with technical leadership and team development. This is not a purely managerial position. You'll remain closely involved in developing, training, evaluating, and deploying ML models, while helping shape technical direction and supporting the growth of the wider engineering team.
What You'll Be Doing
- Providing technical leadership to a team of Machine Learning Engineers, supporting their development through mentoring, coaching, and technical guidance.
- Leading the design, development, training, and deployment of machine learning and deep learning models.
- Taking ownership of complex ML projects from initial research and experimentation through to production deployment.
- Driving applied research, evaluating new approaches, and translating promising techniques into practical engineering solutions.
- Working on ML systems deployed in challenging environments, including Edge and embedded platforms with constrained computing resources.
- Developing and optimizing models for accuracy, inference performance, latency, and reliability.
- Establishing robust model evaluation, benchmarking, and testing approaches.
- Supporting ML infrastructure, training pipelines, experiment tracking, and deployment processes.
- Collaborating with software, hardware, and systems engineers to integrate ML capabilities into wider technology platforms.
- Helping define technical standards, engineering best practices, and the longer-term direction of the ML capability.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What We're Looking For
We're interested in experienced ML Engineers who have progressed into Principal, Staff, Lead, or technical leadership positions, or who are ready to take that next step.
Essential experience:
- Strong commercial experience developing, training, and deploying machine learning or deep learning models.
- Excellent Python programming skills and a strong understanding of software engineering principles.
- Deep technical knowledge of machine learning, neural networks, model architectures, and optimization.
- Experience with ML frameworks such as PyTorch, TensorFlow, or equivalent.
- Proven ability to take ML solutions from research or prototype stage into production.
- Experience providing technical leadership, mentoring engineers, or taking ownership of complex engineering projects.
- Strong understanding of model evaluation, performance optimization, and production ML challenges.
- Ability to work collaboratively with multidisciplinary engineering teams.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Particularly interesting experience:
- Computer vision, object detection, sensor fusion, or sequence modelling.
- Applied ML research and experimentation.
- Edge AI, embedded ML, or deploying models onto constrained hardware.
- Model compression, quantization, inference optimization, or distributed training.
- LLMs, foundation models, fine-tuning, and model evaluation.
- GPU computing and large-scale model training.
- MLOps, MLflow, Docker, Kubernetes, or cloud-based ML infrastructure.
- Previous experience leading or mentoring Machine Learning Engineers.
You don't need experience across every area. We're particularly interested in candidates with genuine depth in one or more ML disciplines and the ability to apply that expertise to challenging engineering problems.
Interested? Apply directly or get in touch for a confidential discussion about the role, technical challenges, and team.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Location