Research Engineer, Optimization

March 15

Helm.ai

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Helm.ai is building the next generation of AI technology for automation.

11 - 50

Description

• 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

Requirements

• 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

Benefits

• 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