Staff Software Engineer, Helm.ai
$150-250k
AI drive assistance systems, autonomous driving, and robotics
Open for applications
AI drive assistance systems, autonomous driving, and robotics
21-100 employees
Open for applications
$150-250k
21-100 employees
Company mission
To prove cutting-edge AI software that empowers automakers and Tier 1 suppliers to launch the world's safest and most advanced L2 through L4 autonomous driving systems at scale.
Role
Who you are
- 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
What the job involves
- 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
- 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
Our take
Automakers are in a race to produce the best self-driving vehicle systems to future-proof their businesses, and the key focus depends on the development of hardware such as radar and video sensors. Whilst these produce essential data required for autonomous vehicles to assess their surroundings, the industry lacks a software framework for the analysis of this data to improve self-driving capabilities.
Helm.ai develops software that aims to understand sensor data in the same way that humans can assess information whilst driving a car manually. Uniquely, this software uses machine learning to train neural networks without the need for on-road testing and manual data analysis, in an attempt to increase the rate of self-driving vehicle development and reduce the costs required to do so.
The autonomous vehicle sector has had its fair share of bumps, from regulatory challenges to underperforming publicly listed companies. But there's still a massive opportunity, especially for long-haul fleets. In 2024, Helm.ai introduced a range of products designed to meet these specific needs. And, with its cutting-edge technology and expertise, it's perfectly positioned to bring autonomous vehicles to market and support the future of transportation in these growing markets.
Freddie
Company Specialist at Welcome to the Jungle
Insights
46% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Aug 2025
$10m
LATE VC
Aug 2023
$55m
SERIES C
Total funding: $145m
Company benefits
- Comprehensive health, dental, and vision insurance for you and your dependents, with up to 100% of premiums paid by the company for employees
- Monthly wellness stipends
- 401(k) plan management
- Free lunch and fully-stocked kitchen in our Redwood City office
- Office setup allowance
- Company retreats
- … and more to come as we scale!
Company HQ
Redwood City, CA
Leadership
Vlad Voroninski
(CEO & Founder)Graduated with a PhD from UCD Berkeley before working as an MIT Postdoctoral Fellow and a Sift Security Chief Scientist for a year. In November 2016, they co-founded Helm.ai, serving as CEO ever since then.
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