Senior Computer Vision Specialist

Locations Portfolio Investors Insights About Residency Portfolio Company Opportunities Join a Startup, Change the World Career Opportunities at Antler Senior Computer Vision SpecialistSortraceSoftware Engineering, IT, Data Science · Full-timeRemotePosted on May 20, 2026About us Sortrace builds camera-based perception for waste collection vehicles. We turn video from collection operations into insights that help municipalities and waste operators understand sorting quality, contamination, and safety-relevant items. The domain is visually messy, policy- driven, and deployed in the real world, not a clean lab benchmark. The role We want a senior applied computer vision specialist who can help us define and ship the next generation of our perception stack. We are not prescriptive about model family or headline architecture: we expect to explore several directions and pick what actually meets our accuracy, latency, cost, and maintainability constraints. The role can be structured as a f ull-time hire (lead-level) or a multi-month advisory / contracting engagement, depending on the person and timing. What you will work on Architecture and roadmap: compare credible options for detection, classification, and segmentation under our data and deployment constraints, including how each path fits what we already operate in production. From research to production: turn experiments into something we can operate, monitor, and improve over time. Evaluation: help define how we measure quality so improvements are defensible, not just leaderboard scores. Deployment reality: whatever we choose must survive embedded-class hardware on vehicles, variable lighting and motion, and multi-camera setups. You should be comfortable reasoning about throughput, memory, and reliability, not only offline training metrics. Uncertainty and human-in-the-loop: where the product needs calibrated confidence, review workflows, or active learning, you help make that explicit in the system design. Must-have experience Shipped computer vision in production (not only papers or Kaggle); you know what breaks when models leave the notebook. Hands-on strength across training, evaluation, and deployment tooling; you can own an end-to-end slice without waiting for a separate "MLOps person." Breadth across model families: real project experience with both convolutional and transformer-based vision approaches; you are not married to one camp. Architectural judgment: a deep understanding of the trade-offs, failure modes, and limitations of different models and architectures, and the ability to argue for one over another given concrete constraints. Resource-aware ML: meaningful experience getting models to run well under tight compute budgets (embedded GPUs, mobile, or other constrained targets, not only datacenter batch jobs). Sound experimental judgment: you can propose hypotheses, define success criteria, and kill dead ends quickly. Stack fluency: comfortable in Python and the PyTorch ecosystem. Specific tooling within that is something we expect to revisit together. Nice to have Hands-on experience deploying on edge platforms. Domains with clutter, occlusion, and long-tail objects (e.g. waste, logistics, agriculture, robotics). Fleet or field deployment: versioning, staged rollouts, monitoring, safe rollback. European privacy and data-residency awareness in product design. Public contributions or maintainership in widely used CV / ML codebases. Engagement Location: Remote within Europe is fine; Nordic time zones are easiest for day-to-day collaboration. Shape: Open to f ull-time senior/lead hire or a scoped advisory or contract. A short paid pilot before a longer commitment is possible if both sides want it. What we offer Equity: Meaningful ownership - you share in the upside as we grow. Real-world impact: The work ends up on vehicles in the field, not in a benchmark. What you build affects how...