We 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 focus on research and development related to the optimization of ML models on GPU’s or AI accelerators. You will use your judgment in complex scenarios and apply optimization techniques to a wide variety of technical problems. Specifically, you will:
- Research, prototype and evaluate state of the art model optimization techniques and algorithms
- Characterize neural network quality and performance based on research, experiment and performance data and profiling
- Incorporate optimizations and model development best practices into existing ML development lifecycle and workflow.
- Define the technical vision and roadmap for DL model optimizations
- Write technical reports indicating qualitative and quantitative results to colleagues and customers
- Develop, deploy and optimize deep learning (DL) models on various GPU and AI accelerator chipsets/platforms
You have:
- Proficiency in ML model development and optimization techniques (e.g. numerical optimization, quantization, pruning, architecture search and design), particularly on model deployment onto GPU’s or AI accelerators
- Strong understanding of deep learning algorithms, software engineering and GPU-based computing
- Proven ability to thrive in fast-paced environment
- Ability to communicate complex technical concepts to colleagues and a variety of audience
- Introspection, thoughtfulness, and detail-orientation
- Proficiency in Python
The following are a plus, but not required:
- Master’s or Ph.D. in a related field and/or 5+ years of experience in a directly related field
- Experience working with neural networks, Tensorflow and/or PyTorch
- Computer vision experience
The pay range for this position is estimated to fall in the base range of approximately $150,000 and $250,000. Base compensation for this position will vary based on location, qualifications, and relevant experience. The offered base salary may be above or below this range and compensation for the position may include additional compensation in the form of equity or a bonus/commission.
- 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
