Research Engineer

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