Senior Software Engineer
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.
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.
You will
Work closely with research engineers to develop productionized ML workflows
Develop and iterate on platform infrastructure for training, validating, and deploying neural networks
Deploy cloud infrastructure and build distributed data-processing pipelines
Develop on an in-house multi-tenant data lake ecosystem supporting the entire lifecycle of machine learning operations
Build internal APIs to serve data, trigger workflows, enforce business logic, etc.
Build CI/CD process and other internal tools to enhance developer productivity
You have
Strong programming experience demonstrated via work experience, internships, or programming competition performance.
Deep knowledge of dev-ops and infrastructure processes such as infra-as-code, microservice deployment, software networking, build tool management
Previous experience in a data-heavy role, such as data infrastructure or machine learning engineer.
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
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
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.
Strong programming and dev-ops experience, infra-as-code and distributed systems knowledge, experience with data infrastructure or machine learning workflows.
Key Responsibilities
- developing workflows
- deploying infrastructure
- building pipelines
Skills & Tools
infra-as-code, CI/CD
Job Details
- Category: Software Development
- Seniority: Senior Level
- Commitment: Full Time
- Workplace: Remote — United States or California
- Salary: USD 150,000 – 250,000 / year
- Languages: English
Benefits
- Retirement plan
About Helm.ai
A company that builds AI software to enable autonomous driving and robotics, focusing on data-efficient training methods. — Industry: Information Technology