Senior Machine Learning Engineer

The video security market ($50B+ by revenue) is dominated by incumbents, with less than 1.5% of the companies using a cloud-based video security solution. However, most companies see cloud video security as the future and want to move to the cloud. This AI startup provides a modern cloud software interface for video security that works with any IP camera and takes only 10 minutes to deploy. With this company, a user can type what they are looking for, and this AI startup analyses all the recorded data to find it in seconds. They have deployed thousands of cameras across many customers in the US and is on the path to managing one of the largest networks of cloud-connected cameras. This is a great time to join the team.

Team

Founded by Ashesh (CEO) and Peter (CTO), we are serial entrepreneurs and experts in AI and robotics. Our engineering team comprises industry experts with decades of research and experience from Lyft, Google, Zoox, Toyota, Facebook, Microsoft, Stanford, Oxford, and Cornell. Our go-to-market team consists of experienced leaders from Verkada. We are venture-backed by 8VC, revenue-generating, and have multiple years of runway.

 

Why should you consider this company?

• Very interesting and challenging problem: we are on the path to managing one of the largest distributed networks of cameras for physical security and likely crossing 100,000 cameras in the future. The code you write will be shipped to many physical devices.
• Leverage the latest advances in foundation models and LLMs: leverage multi modal foundation models to make millions of video logs collected from security cameras searchable and build a physical security AI agent.
• We have a product that customers really like and pay for a multi-year license upfront. We make a profit on each deployment.
• 100% of customers prefer this tooling over the competition after a demo
• The market for this is massive and growing (projected to reach $85.5 billion by 2026)
• We are well-funded and still very early. Expect a meaningful equity ownership that will compound over the years.
• Lead projects from Day 1.

 

The role

We are hiring a full-stack machine learning engineer. This is an in-office role in Sunnyvale, CA. We are an early-stage startup, so everyone is expected to work very hard.

 

• Take an existing open-source Pytorch model, productionize them in C++ runtime, and optimize for latency and throughput.
• Take an open-source model and fine-tune them on our in-house data set as needed.
• Design thoughtful experiments in evaluating the tradeoffs between latency and accuracy on the end customer use case.
• Integrate the model with the downstream use case and fully own the end metrics.
• Maintain and improve all existing ML applications in the product
• Read research papers and develop ideas on how they could be applied to video security use cases, and convert those ideas to working code.

 

Requirements

• You should be a good software engineer who enjoys writing production-grade software.
• At least 3+ years of industry experience in productionizing ML models.
• Strong machine learning fundamentals (linear algebra, probability and statistics, supervised and self-supervised learning)
• Keeping up with the latest in deep learning research, reading research papers, and familiarity with the latest developments in foundation models and LLMs
• Comfortable with productionzing a Pytorch model developed in C++, profiling the model for latency, finding bottlenecks, and optimizing them
• Good understanding of docker and containerization
• Experienced with Pytorch and Python3, and comfortable with C++
• (Good to have) Understanding of Torch script, ONNX runtime, TensorRT
• (Good to have) Understanding of half-precision inference and int8 quantization
• (Good to have) Experience with Robotics, or autonomous vehicles

 

Benefits

• Medical, Dental, and Vision insurance
• 401k (no matching)
• Good equity ownership in the company