Senior Machine Learning Engineer

Role overview Build the cloud-side ML backend that turns trained safety models into reliable, low-latency features running across millions of edge devices. This is a senior engineering role focused on what happens after a model is trained: serving, evaluation, monitoring, and continuous iteration at fleet scale. You will work across applied science, firmware, platform engineering, and product to ship systems where rare, high-consequence events have to be detected correctly.

Responsibilities - Architect and maintain low-latency ML APIs that surface safety model outputs to downstream cloud applications. - Productionize model artifacts handed off by applied scientists, including serving logic, optimization, and platform-specific tuning. - Build scalable data pipelines for backtesting, shadow and online evaluation, and automated dataset curation across petabytes of camera and sensor telemetry. - Implement monitoring for model drift, precision and recall regressions, and latency regressions, with predictable failure modes and closed-loop feedback. - Partner with firmware and platform teams to balance edge-to-cloud latency, throughput, and infrastructure cost. - Define practical standards for how models are served, versioned, evaluated, and rolled out across the product surface.

Requirements - 6+ years of experience as a machine learning engineer or similar role, with a track record of shipping models to production. - Strong proficiency in one or more backend or systems languages used to build ML platforms and APIs. - Deep experience with model serving, CI/CD for ML systems, and production evaluation infrastructure. - Familiarity with large-scale data processing across petabyte-scale telemetry or sensor streams. - Comfort working with applied scientists and translating research outputs into debuggable, cost-efficient production systems. - Experience partnering with product, firmware, and platform engineering on cross-cutting launches.

Benefits and work setup - Remote role open to candidates residing in the US or Canada. - Benefits package referenced includes a professional development stipend, comprehensive health coverage, and parental leave plans.