Research and develop optimization techniques for ML models on GPUs and AI accelerators, while evaluating model quality and integrating best practices into development workflows.
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:
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, sparsity, 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
- Experience working with neural networks in Tensorflow and/or PyTorch
- 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
- Computer vision experience
We offer:
- Competitive health insurance options
- 401K plan management
- 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
Helm.ai is proud to be an equal opportunity employer building a diverse and inclusive workforce. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Any unsolicited resumes/candidate profiles submitted through our website or to personal email accounts of employees of Helm.ai are considered the property of Helm.ai and are not subject to payment of agency fees.
Similar Jobs
Artificial Intelligence • Software
The role focuses on optimizing AI models for efficiency, involving GPU/CPU code profiling, high-performance programming, and developing performance tools.
Top Skills:
CudaNvidia NsightOnnxPyTorchTensorrtTorch ProfilerTritonXla
Artificial Intelligence • Cloud • Information Technology • Machine Learning • Natural Language Processing • Software
The Localization Project Manager will manage end-to-end localization processes for enterprise clients, ensuring workflow optimization, problem-solving, and client relationship management in a remote environment.
Top Skills:
AIAsanaCat ToolsGoogle SheetsJIRALookerSmartlingTms
Artificial Intelligence • Big Data • Healthtech • Machine Learning • Analytics • Biotech • Generative AI
The role involves supporting research collaborations in oncology, engaging KOLs, managing study proposals, and contributing to medical writing and strategy development.
Top Skills:
AIGenomic Testing
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
