Computer Vision

Location: Zurich, Switzerland |Team: Engineering |Type: Full-TimeAt AVIAN (avian-), our mission is clear: we stop fires before they start. Our advanced infrared camera systems and AI-driven monitoring solutions help manufacturers protect people, assets, and the environment from devastating fire risks. Partnering with global insurers and industry leaders, we deliver technology that safeguards critical operations and builds a culture of safety across the wood, manufacturing, and energy sectors.Why this role mattersThis isn't research for slides—it's mission-critical engineering. You'll design, build, and deploy the algorithms that keep entire facilities safe. When our system fails, real operations are at risk. If that pushes you rather than deters you, this is your place.What you'll doEngineer and optimize CV/ML pipelines in Python and C++ for real-time inference on embedded and Linux-based edge devices.Deploy at scale on embedded hardware and in the cloud.Fuse multimodal data (thermal, RGB, signal-based) and integrate LLM-powered models for detection, scoring, and anomaly analysis.Own the lifecycle: from early-stage research to production rollout, monitoring, and post-deployment improvements.Raise the bar: conduct reviews, mentor teammates, and set technical direction across the CV/ML stack.How success is measuredReal-time performance meets or exceeds production KPIs (latency, precision, recall).Stable AWS deployments with zero-rollback production updates.Documented model improvement metrics across successive releases.Measurable decrease in alarms caused by nuisance phenomena like exhausts, chainsaws, welding, etc.Field devices operate autonomously for >30 days with zero human intervention.What you bringMust-Haves:5+ years in software or ML/CV engineering with full-lifecycle ownership—from concept to deployed system.Expert in Python and C++, with a deep understanding of performance optimization for CV workloads.Hands-on with Linux, embedded systems, and resource-constrained inference.Strong foundation in OpenCV, PyTorch, or TensorFlow.Proficient in AWS (Lambda, ECS, EC2, S3, SageMaker).Nice-to-Haves:Experience with CLIP, LLaVA, or other vision-language models.Publications in top-tier ML/CV venues (CVPR, ICCV, ECCV, NeurIPS, ICLR) demonstrating research depth.Proven record of shipping ML products from cradle to grave—prototype, optimize, deploy, and maintain.Familiarity with MLOps/DevOps (Docker, CI/CD, Grafana, Prometheus).Open-source contributions or notable ML projects.M.Sc. or PhD in ML, CV, or Robotics.Who you areObsessed with real-world impact and technical rigor.Self-directed, accountable, and driven to deliver without supervision.Thrives at the intersection of CV, cloud, and embedded systems.Understand that "production" means lives and assets depend on your code.Willing to work long hours when needed—you don't clock out when the system's at risk. Do not apply if you're looking for balance over mission.Our technology protects lives and livelihoods—reliability isn't optional. Expect intensity, ownership, and pace.What we offerHigh-ownership engineering: your work directly prevents fires and saves lives.Fast, flat, and transparent: no silos, no fluff, just impact.Flexible hours with full trust.Attractive equity participation: share in AVIAN's growth.30/60/90-Day Plan30 Days - Foundation & Ramp-Up:Replicate one end-to-end CV pipeline from repo to edge deployment.Profile thermal and RGB models on real hardware; benchmark latency and memory.Deliver one performance or inference optimization patch.60 Days - Ownership & Delivery:Take ownership of a core subsystem (motion analysis, temporal filtering, or anomaly detection).Deploy your subsystem via AWS ECS + Lambda orchestration.Provide reproducible benchmarks showing measurable improvement.90 Days - Production Leadership:Lead a live production rollout and post-deployment validation.Implement automated monitoring with error metrics and alerting.Deliver a concise design doc or internal paper establishing new performance standards.How to applyEmail - with subject: "CV/ML Engineer - [Your Name]"Include:Your CV or LinkedIn.A short note describing one ML/CV system you shipped end-to-end and the results it achieved.Links to publications, GitHub, or demos showing your real-world impact and the stuff you build in your free time. If you aren't obsessed, do not apply.