NearTech Search
Senior Computer Vision & Face Recognition Engineer

How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Senior Machine Learning Engineer - Computer Vision & Face Recognition
Location: UK Remote / Hybrid
Level: Senior - 5+ years' production Computer Vision / ML experience
The Opportunity
An exciting opportunity to take ownership of a production-grade facial recognition and Computer Vision platform, from model development through to deployment on NVIDIA edge hardware.
This is not a research-only role. You'll take models from development through to real-world deployment, working across face detection, alignment, embedding models, matching and evaluation, while balancing accuracy, performance and real-world constraints. You'll have genuine ownership of the face recognition capability and the opportunity to shape how the technology is built, evaluated and deployed.
What You'll Do
- Build and develop the full face recognition pipeline - detection, landmarks, alignment, quality filtering, embeddings and matching.
- Train, fine-tune and evaluate face embedding models, including decisions around training data and loss functions.
- Develop evaluation frameworks for 1:1 verification and 1:N identification, including FAR/FMR, FNMR, TAR and threshold selection.
- Build multi-camera Computer Vision pipelines for real-world deployment.
- Deploy and optimise models on NVIDIA edge GPUs, using ONNX, TensorRT and FP16/INT8 quantisation.
- Work with NVIDIA DeepStream to maximise real-time video processing performance.
- Design gallery and enrolment systems, including indexing, similarity search, template management and thresholding.
- Work closely with data protection and legal teams to build responsible biometric systems, including retention, auditability and privacy requirements.
- Benchmark and track model performance across releases.
- Review technical work and mentor mid-level engineers.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt 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.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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
- 5+ years' production Computer Vision / Machine Learning experience.
- Proven experience building and deploying facial recognition systems using learned embeddings.
- Strong understanding of face detection, landmark alignment and embedding approaches such as ArcFace, CosFace or AdaFace.
- Strong understanding of 1:1 verification vs 1:N identification and biometric evaluation metrics.
- Strong Python, with C++ experience or willingness to work with it.
- PyTorch for training and ONNX/TensorRT for production deployment.
- Hands-on NVIDIA GPU, CUDA and inference optimisation experience.
- Docker, Linux, Git and CI/CD experience.
- Comfortable making technical decisions based on measurable accuracy and performance.


Get help with your application
Your very own career expert that helps elevate your application to the next level.
Particularly Relevant Experience
- Facial recognition using CCTV or challenging real-world imagery, including low-resolution, off-angle faces, motion blur, occlusion and difficult lighting.
- NVIDIA DeepStream, GStreamer or Triton.
- Face quality assessment and template fusion.
- FAISS, HNSW or
“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