Computer Vision Engineer

Computer Vision / ML Optimisation Engineer - Manchester - £70,000 - £90,000

We're working with a high-impact UK organisation driving real-time AI innovation across edge and GPU-accelerated systems. As part of a forward-looking expansion into 2026, they're strengthening their AI deployment capabilities to power faster, leaner model performance at scale. This is a rare chance to shape the tech direction before the team fully scales - ideal for someone who thrives in deep-tech environments where theory meets hardware.

The engineer will join a specialist function focused on refining model performance, optimising inference, and enabling low-latency deployment across diverse compute platforms.

Role Highlights

You'll work on:

– Optimising deep learning models through quantisation, pruning, and fine-tuning

– Evaluating architectures for speed/accuracy trade-offs across devices

– Exporting models for runtime use (e.g. ONNX, TorchScript)

– Supporting research-to-deployment workflows that accelerate iteration

– Helping define a scalable ML pipeline for edge and embedded use

You'll bring:

– Proven experience in CV/ML model optimisation and deployment

– Knowledge of TensorRT, ONNX Runtime or similar inference runtimes

– Hands-on experience with CUDA, low-latency profiling and C++ integration

– Strong command of model export tools and deployment best practices

– A performance-first mindset and confidence in debugging at system level

Why them?

– Strong base salary

– Hybrid working with flexible remote days

– Work at the intersection of research, AI systems, and deployment

– Clear progression as the 2026 expansion builds out

– Contribute to real-world AI acceleration that moves beyond the lab/demo stage

Notes:

Please note this role cannot offer visa sponsorship now or in the future. This is a hybrid role from Manchester city centre (2 days per week), candidates not based within a commutable distance will not be considered.

Job Details

Company
NearTech Search
Location
Bolton, Greater Manchester, UK
Hybrid / Remote Options
Employment Type
Full-time
Posted