Helm.ai

• Lead and Build: Architect and design scalable, reliable, and efficient ML infrastructure and services, enabling the company to handle large scale training, massive datasets, and a growing number of customers with diverse needs. • Scale Systems: Ensure the ML platform is capable of handling large-scale data processing and machine learning model development at a global scale. • Agility & Cost Efficiency: Optimize platform implementation for flexibility and cost-effectiveness while maintaining agility in development, enabling quick adaptation to evolving requirements. • User-Centric Design: Build systems that are convenient, reliable, and easy to use for both internal teams (data scientists, engineers) and external customers. • End-to-End Ownership: Take full ownership of the platform's lifecycle, from inception through design and implementation to deployment and monitoring. • Collaboration: Work closely with cross-functional teams, including data science, product, and operations, to ensure seamless integration of ML capabilities into business-critical services. • Innovation: Keep up with the latest industry trends and incorporate cutting-edge technologies into our platform to maintain a competitive edge. • Problem-Solving: Tackle complex technical challenges head-on, from infrastructure optimization to providing solutions for data processing, storage, and access at scale. • Mentorship: Lead and mentor engineers, fostering a culture of excellence and high-performance within the engineering team.

You will collaborate with researchers to perform research operations using existing infrastructure. You will use your judgment in complex scenarios and help apply standard techniques to a wide variety of technical problems. Specifically, you will: - Characterize neural network quality, failure modes, and edge cases based on research data - Maintain awareness of current trends in relevant areas of research and technology - Coordinate with researchers and accurately convey status of experiments - Manage a large number of concurrent experiments and make accurate time estimates with respect to deadlines - Review experimental results and suggest theoretical or process improvements for future iterations - Write technical reports indicating qualitative and quantitative results to external parties You have: - A sense of practical optimism: not all experiments are successful, but the ones that are more than make up for it! - Proficiency in Python - 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 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 reading research papers and implementing the techniques therein - Computer vision and deep learning 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. 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.

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.

• Focus on research and development related to the optimization of ML models on GPU’s or AI accelerators • Use judgment in complex scenarios and apply optimization techniques to a wide variety of technical problems • 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

• Collaborate with researchers to perform research operations using existing infrastructure • Use judgment in complex scenarios and help apply standard techniques to a wide variety of technical problems • Characterize neural network quality, failure modes, and edge cases based on research data • Maintain awareness of current trends in relevant areas of research and technology • Coordinate with researchers and accurately convey status of experiments • Manage a large number of concurrent experiments and make accurate time estimates with respect to deadlines • Review experimental results and suggest theoretical or process improvements for future iterations • Write technical reports indicating qualitative and quantitative results to external parties

• Work collaboratively to improve our models and iterate on novel research directions • Apply and extend the Helm proprietary algorithmic toolkit for unsupervised learning and perception problems at scale • Carefully execute development and maintenance of tools used for deep learning experiments designed to provide new functionality for customers or address relevant corner cases in the system as a whole • Work closely with software and autonomous vehicle engineers to deploy algorithms on internal and customer vehicle platforms

• Collaborate with researchers to perform research operations using existing infrastructure • Use judgment in complex scenarios and help apply standard techniques to a wide variety of technical problems • Characterize neural network quality, failure modes, and edge cases based on research data • Maintain awareness of current trends in relevant areas of research and technology • Coordinate with researchers and accurately convey status of experiments • Manage a large number of concurrent experiments and make accurate time estimates with respect to deadlines • Review experimental results and suggest theoretical or process improvements for future iterations • Write technical reports indicating qualitative and quantitative results to external parties

• You will work collaboratively to improve our models and iterate on novel research directions, sometimes in just days. • Apply and extend the Helm proprietary algorithmic toolkit for unsupervised learning and perception problems at scale • Carefully execute development and maintenance of tools used for deep learning experiments designed to provide new functionality for customers or address relevant corner cases in the system as a whole • Work closely with software and autonomous vehicle engineers to deploy algorithms on internal and customer vehicle platforms

• Focus on research and development related to the optimization of ML models on GPU’s or AI accelerators • 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