At Cerrion, we’re building the future of AI-enabled manufacturing. Headquartered in Zurich and backed by Y Combinator and top Silicon Valley investors, we’re building a platform to deploy video AI Agents that can see what’s happening on the production floor, automatically spot problems, and instantly intervene to keep lines running smoothly, at scale. Our technology is live in factories across 15 countries, helping leading manufacturers in glass, beverage, food, CPG, building materials and wood cut downtime by up to 50%. We’ve reached an exciting inflection point — and we’re accelerating fast.

We’re hiring an Applied Researcher to set and execute the research agenda for Cerrion’s video‑AI platform and turn bold hypotheses into measurable gains in accuracy, robustness, and latency. We’re looking for a superstar who brings founder‑style ownership across the end‑to‑end research lifecycle — problem framing, data curation, rapid prototyping, experiment design, and rigorous evaluation — balancing scientific depth with pragmatism and a strong bias for shipping. You’ll work directly with our founders and the research team to prioritize the research roadmap, run a fast and reproducible experiment pipeline, and partner with Engineering to turn promising ideas into production‑ready models.

• Run Fast, Reproducible Experiments: Design and run searches; keep configs, seeds, and artifacts tidy for one‑click reruns.
• Diagnose Bad Runs: Trace failures across data, augmentations, labels, and training dynamics; implement quick fixes and verify with targeted evals.
• Curate & Improve Data: Define datasets, create focused error sets, manage sampling/imbalance, and partner on labeling/QA to close the loop.
• Own Evaluation: Build and maintain a rigorous eval suite (accuracy/robustness/latency/cost), plus small dashboards for trend tracking and failure clustering.
• Prototype to Production: Convert promising ideas into production‑ready models in partnership with Engineering (tests, packaging, canary, monitoring).
• Optimize for Cost & Latency: Profile training/inference, choose efficient architectures, and keep GPU hours and serving budgets in check.
• Communicate Clearly: Make sure the experimental environment is clean and documented so that the experimental knowledge is well-preserved.
• Build the Function: Establish research hygiene (coding standards, review, documentation) and help shape hiring as the team grows.

• Applied ML/CV Experience: 2–5+ years working with real‑world models (images or video), Kaggle experience would be a plus.
• Relevant education: Masters or PhD in Computer Science or related field with strong computer vision or machine learning understanding.
• Strong Python + PyTorch: Comfortable writing clean training/eval loops.
• Experiment Operations: Hands‑on with ML experiment platforms (ClearML, Weights & Biases, etc.)
• Data‑Centric Mindset: Practical know‑how in augmentations, class imbalance, sampling strategies, label quality, and active‑learning basics.
• Evaluation Rigor: Fluency with mAP/F1/IoU/ROC‑PR, calibration, robustness tests, and dataset/version management for reproducible comparisons.
• Collaboration & Writing: Able to turn findings into clear recommendations and work closely with Engineering, Product, and GTM.

• Video & Tracking: Experience with temporal models (2D/3D CNNs, transformers), multi‑object tracking, motion/occlusion handling.
• Foundation/Multimodal: Familiarity with CLIP‑style pretraining, VLM adapters/LoRA, or lightweight finetuning of foundation models.
• Scale & Search: Distributed training (DDP/FSDP), HPO frameworks (Optuna/Ray Tune), and thoughtful compute budgeting.
• Model Optimization: Distillation, pruning, quantization; deployment with ONNX Runtime/TensorRT; edge/real‑time constraints a plus.
• Data Tooling: Labeling ops, weak supervision, synthetic data generation/augmentation pipelines.
• Domain Context: Prior work in video analytics for industrial or safety‑critical environments.

• Ownership & impact: Define and run the research that matters for solving critical real world problems. Your work will shape the future of autonomous manufacturing.
• Growth path: This role is designed to evolve into Head of Product as you build out the team and processes.
• Culture: We operate with flat hierarchies and a get‑things‑done mentality. You’ll work with ambitious colleagues from all over the world in a collaborative environment where the best idea wins.
• Compensation & equity: Competitive salary, meaningful stock option package and comprehensive benefits.
• Location: Modern office in the heart of Zurich; enjoy the quality of life of Switzerland and the dynamics of a high‑growth startup.

If you’re passionate about building computer vision systems that work even in the toughest environments, we would be excited to meet you!