Software Engineer, Machine Learning Operations
Blissway · Denver, Colorado
About this role
**Software Engineer, Machine Learning Operations** **About Blissway** A startup simplifying toll collection and improving highway safety through Deep Tech, AI/ML, Hardware, SaaS, and IoT. Processing 11 million images daily across the US Interstate Highway System with a lean team of under 30. **The Role** Own the infrastructure that takes ML models to production and keeps them running reliably. You'll manage training/serving infrastructure, model versioning, deployment, monitoring, and updates for systems processing massive scale vision data across vehicles, license plates, wheels, and lane markings. **Key Responsibilities** • Build and maintain production ML infrastructure (training, serving, versioning, deployment) • Monitor model performance and catch degradation before it impacts operations • Deploy models to both cloud and edge/resource-constrained hardware • Manage real-world systems running on roadside hardware, not just test environments • Own the full lifecycle: from notebook to production to continuous updates **You're a Good Fit If** ✓ 2-6 years building and running production systems (infrastructure, backend, ML platforms) ✓ Write production-quality code with strong fundamentals in pipelines, deployment, observability ✓ Understand ML model training/evaluation well enough to debug in production ✓ Comfortable with ownership, detail-oriented, adaptable to lean team needs ✓ Bonus: Experience with model deployment, edge hardware, or self-managed servers **What We Offer** 💰 Competitive equity, transparent compensation, 401(k) matching (4%) 🏥 Personalized health coverage (ICHRA) 🏢 Denver office with relocation support 🌴 4 weeks untracked PTO + 12-week paid parental leave + 5-year sabbatical (12 weeks paid) 🍽️ Daily team lunches, fully stocked kitchen 🎮 Team events, annual 4-day BlissTrip, continuous learning budget **Interview Process** 3-4 interviews + paid work trial. Direct access to technical leadership from day one.
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