Computer Vision Engineer - Applied AI / Production ML (Hybrid)

We’re partnering with a fast-growing, venture-backed AI company building computer vision systems deployed directly into real-world, operational environments.

This is a high-impact engineering role, not a research position. You’ll be working on applied computer vision problems where performance, robustness, and real-world usability matter, not just model accuracy on paper

.
If you enjoy taking models from idea through to production and real usage, this is the kind of environment where your work will have immediate impac

t.
What you’ll be doi

• ng:Building and deploying computer vision models into production environme

ntsWorking on practical challenges such

• as:Image segmentat
• ion2D object detect
• ionModel performance and optimizat
• ionIterating on models, experimenting, validating approaches, and improving performa
• nceWriting clean, production-ready code as part of a broader platf
• ormCollaborating closely with end users to understand real-world problems and translate them into working soluti

ons
Your backgro

• und:2+ years’ experience in applied computer vision / machine lear
• ningStrong Python skills with libraries such
• as:PyTorch / Tensor
• FlowOp

enCVHands-on experience w

• ith:Image segmenta
• tionObject detection (e.g. YOLO, UNet-style mod
• els)A track record of taking models beyond proof-of-concept into production or near-production environm
• entsSomeone who experiments, iterates, and improves models, not just implements a single appr

oach
Strong

• plusExperience working on real-world datasets and messy environ
• mentsStartup or small-team experience with high owne
• rshipExposure to model optimisation and performance t

uning
What this

• isn’tNot a research-heav
• y roleNot focused on robotics, 3D vision, or purely academi
• c workNot suited for candidates who prefer theory over bu

ilding
Why this role sta

• nds outYour work is deployed into real operational environments, not left in no
• tebooksHigh ownership, small team, meaningful impact from
• day oneStrong backing and clear growth tra
• jectoryEquity and competitive compe
• nsationPragmatic, execution-focused engineering