Senior Staff Software Engineer (VMS/ML)

Job Title: Senior Staff Engineer – Cameras, Streaming, or ML Focus

Team: Core Engineering

Level: Senior / Staff

We're currently looking for a Senior or Staff Engineer to take technical ownership of one of two key domains:

• Video / Camera Infrastructure (RTSP, HLS, encoding, live streams)
• Applied Machine Learning (real-time inference, model optimization, edge ML)

If you're a systems-minded engineer who gets excited about video pipelines or the practical application of ML in production—let's talk.

Cameras & Streaming Focus

What You’ll Do

• Architect and scale infrastructure for ingesting and processing live video feeds (RTSP, HLS, WebRTC, etc.)
• Build systems for real-time and historical video playback, storage, and transcoding
• Work closely with product and ops teams to integrate diverse camera hardware into a reliable and maintainable pipeline
• Own encoding performance and video latency optimizations
• Drive improvements in monitoring, quality of service, and incident response around video infrastructure

What We're Looking For

• Deep understanding of video streaming protocols (RTSP, HLS, MPEG-DASH, etc.)
• Strong systems engineering skills—networking, low-latency services, concurrency
• Experience working with video codecs (H.264, H.265, etc.) and tools like FFmpeg or GStreamer
• Familiarity with edge device integration or IoT is a bonus
• Ability to debug across complex distributed systems

Machine Learning Focus

What You’ll Do

• Lead development of ML-powered features, from prototype to production
• Optimize inference performance on edge and server-side environments
• Work across data collection, labeling, training, deployment, and monitoring
• Collaborate closely with product and backend teams to ship practical ML solutions
• Influence long-term architecture for ML model management and experimentation

What We're Looking For

• Strong background in machine learning and systems integration
• Experience with real-time or streaming ML pipelines (vision, NLP, etc.)
• Fluency with at least one ML framework (PyTorch, TensorFlow, ONNX)
• Practical mindset—you’ve deployed models, not just trained them
• Bonus: Familiarity with video or image-based ML (e.g. object detection, tracking)

Common Qualifications

• 6+ years of experience in backend, infrastructure, or ML engineering
• Proven ability to lead complex projects with minimal oversight
• Passion for solving real-world problems with elegant, maintainable systems
• Comfortable working in a fast-paced environment and owning outcomes

Tech Stack (FYI)

While we're Node / JavaScript heavy across much of the product, this role is flexible—what matters is your ability to build and ship. We use cloud-native tools, Docker, and a modern dev workflow.

Why Join?

• High-impact role on a small, high-leverage team
• Ownership and autonomy: You’ll drive big pieces of technical architecture
• Work on meaningful real-world systems—whether it’s cameras in the field or models in product
• Competitive comp, remote flexibility.