Staff Software Engineer

Helm.ai

10d•$150,000 - $250,000•Hybrid

About The Position

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. We're looking for a Staff Software Engineer to join our growing team! At Helm.ai, expect a fast-paced environment; you will have significant influence over the company's business and the pace of technical innovation. You will work on cutting-edge technologies, solve complex engineering challenges, and contribute directly to shaping our products and the overall direction of the company. We need people who are organized, able to think on their feet, and can find creative solutions to challenging problems.

Requirements

Proven experience in building and scaling cloud-based infrastructure and services, particularly in machine learning or data-heavy environments.
Expert knowledge of distributed systems, cloud platforms (AWS, GCP, Azure), and technologies like Kubernetes, Docker, and microservices architecture.
Deep experience with building large scale services, and the challenges that come with performance, reliability, and cost at scale.
Demonstrated ability to design and implement cost-effective solutions while balancing performance, security, and scalability.
Solid background in machine learning concepts, e.g., model training and validation.
Strong leadership and collaboration skills, with experience working in an agile development environment and mentoring high-performing teams.
Ability to manage ambiguity and thrive in a fast-paced, evolving environment where priorities shift rapidly.
Passionate problem solver with a focus on building practical, reliable, and efficient systems that can scale in real-world, production environments.

Responsibilities

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.
Ensure the ML platform is capable of handling large-scale data processing and machine learning model development at a global scale.
Optimize platform implementation for flexibility and cost-effectiveness while maintaining agility in development, enabling quick adaptation to evolving requirements.
Build systems that are convenient, reliable, and easy to use for both internal teams (data scientists, engineers) and external customers.
Take full ownership of the platform's lifecycle, from inception through design and implementation to deployment and monitoring.
Work closely with cross-functional teams, including data science, product, and operations, to ensure seamless integration of ML capabilities into business-critical services.
Keep up with the latest industry trends and incorporate cutting-edge technologies into our platform to maintain a competitive edge.
Tackle complex technical challenges head-on, from infrastructure optimization to providing solutions for data processing, storage, and access at scale.
Lead and mentor engineers, fostering a culture of excellence and high-performance within the engineering team.