United States onlyWe help make autonomous technologies more efficient, safer, and accessible.
Helm.ai builds AI software for autonomous driving and robotics. Our "Deep Teaching" methodology is uniquely data and capital efficient, allowing us to surpass traditional approaches. Our unsupervised learning software can train neural networks without the need for human annotation or simulation and is hardware-agnostic. We work with some of the world's largest automotive manufacturers and we've raised over $100M from Honda, Goodyear Ventures, Mando, and others to help us scale.
Our team is made up of people with a diverse set of experiences in software and academia. We work together towards one common goal: to integrate the software you'll help us build into hundreds of millions of vehicles.
You will collaborate with research engineers to build infrastructure to perform research operations and automate the training and optimization of ML models for real-time inference in computer vision applications. Specifically, you will:
- Write frameworks with flexible and modular components to quickly prototype trainings and implement new cutting-edge research ideas
- Build robust and fault-tolerant ML pipelines for running inference on large image and video datasets
- Leverage your knowledge of deep learning frameworks to optimize trainings in terms of GPU utilization, memory, speed, and accuracy
- Design and implement APIs to automate the training and validation of a wide range of ML models for specialized use cases
You have:
- 5+ years of experience in a directly related field
- Experience with tensorflow/pytorch, Jax, or related deep learning framework
- Experience building distributed, scalable software as a service
- Proficiency in Python
- Proven ability to thrive in a fast-paced environment
- Ability to communicate complex technical concepts to a variety of audiences
- Introspection, thoughtfulness, and detail-orientation
The following are a plus but not required:
- Master or Ph.D. in Math, Computer Science or a related field
- Experience in learning and implementing techniques from research papers
- Computer vision experience
- Competitive health insurance options
- 401K plan management
- Remote-friendly and flexible team culture
- Free lunch and fully-stocked kitchen in our South Bay office
- Additional perks: monthly wellness stipend, office set up allowance, company retreats, and more to come as we scale
- The opportunity to work on one of the most interesting, impactful problems of the decade
