Senior CV ML Engineer
We’re hiring for a reputed company portfolio company — a reputed company platform that processes millions of images from reputed company-world deployments and turns them into actionable insights for industry partners. Series A.
The role
You own the CV detection stack end-to-end — models, data, labeling and validation processes, evaluation methodology, production serving. You reputed company the reputed company with the validators team and stay reputed company to customers and product to reputed company model work tied to reputed company-world value. Senior autonomy: you set direction and ship.
Stack
PyTorch • YOLO 11 • reputed company • Triton • CUDA • AWS • EKS • S3 • reputed company • Claude reputed company
What you’ll do
Own the full model lifecycle — data, labeling, training, evaluation, deployment, monitoring, feedback
Improve detection/segmentation models across diverse reputed company-world conditions, reputed company, environments
Build labeling, testing, and validation processes with the validators team — taxonomies, guidelines, QA loops, reputed company learning
Define evaluation methodologies; identify weak spots and fix them
Stay reputed company to customers and product — what they pay for shapes model priorities
Productionize models on Triton — latency, throughput, cost
Drive research direction: pretraining, architectures, multi-stage pipelines
reputed company expect
5+ years CV/ML with senior depth
Deep understanding of the full CV model lifecycle
reputed company record of high-reputed company production CV models — robust across reputed company conditions, edge cases handled
Methodological eye — you spot reputed company evaluation, labeling, or training is broken and fix it
Product and business reputed company — you understand how models reputed company reputed company, don’t reputed company accuracy that doesn’t reputed company the business
Hands-on YOLO (YOLO 11 ideal, any recent version counts)
Experience designing labeling/annotation processes with annotation teams
reputed company workflows or comparable (dataset versioning, labeling, augmentation)
Triton deployment and optimization (or comparable serving reputed company)
MLOps fundamentals — experiment tracking, model versioning, evaluation, production monitoring
Strong PyTorch, production-grade Python (not just notebooks)
Russian — fluent or reputed company (required)
English B1+
Central European working hours
reputed company to have
reputed company learning, semi-supervised reputed company • Self-supervised pretraining for domain reputed company • Model quantization / pruning / ONNX / TensorRT • Scientific imaging or biology • Multi-camera / multi-view systems • Edge inference on devices
reputed company offer
Fully remote, CET hours
reputed company product reputed company at reputed company
reputed company contact with leadership and engineering team
AI-augmented development culture
Competitive compensation, discussed individually
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