Machine Learning Engineer
Posted 1 week ago by SR2 | Socially Responsible Recruitment | Certified B Corporation™
Negotiable
Outside
Undetermined
London Area, United Kingdom
Summary: The role of Machine Learning Engineer involves working on projects that bridge research and practical application in autonomous and defense systems. The position requires expertise in both advanced machine learning development and deployment, with a focus on optimizing models for real-world environments. Candidates must hold active SC or DV clearance and are expected to deliver results in complex settings over a contract period of 6 to 12 months.
Key Responsibilities:
- Support programmes focused on autonomous and defence systems.
- Engage in R&D and neural network development to improve model performance.
- Work on advanced concepts such as spiking neural networks.
- Perform deep technical machine learning problem solving.
- Run models on edge and constrained hardware.
- Optimize inference using tools like TensorRT and compression techniques.
- Integrate machine learning models into real-world systems.
Key Skills:
- Strong Python programming skills.
- Experience with deep learning frameworks such as PyTorch and TensorFlow.
- Proven experience in advanced machine learning development or deployment.
- Ability to deliver in complex, real-world environments.
- Active SC or DV clearance.
Salary (Rate): undetermined
City: London Area
Country: United Kingdom
Working Arrangements: undetermined
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
Contract ML Engineers – R&D OR Edge Deployment (SC/DV Cleared) UK-Based | 6–12 Months | Outside IR35 | Competitive Day Rate
This is ML work at the point where research meets reality. You’ll be supporting programmes focused on autonomous and defence systems, working across either:
- R&D / Neural Network Development
- Improving model performance at architecture level
- Working on advanced concepts (e.g. spiking neural networks)
- Deep technical ML problem solving
- Deployment / Integration
- Running models on edge / constrained hardware
- Optimising inference (TensorRT, compression, etc.)
- Integrating into real-world systems
Across both, you’ll need:
- Strong Python + deep learning experience (PyTorch / TensorFlow)
- Proven experience either in advanced ML development OR deployment
- Ability to deliver in complex, real-world environments
- Must hold active SC or DV clearance
6–12 months (likely extensions as projects scale) UK-based
If you’re a cleared ML engineer and want to work on projects where performance and deployment actually matter - this is worth a conversation.