Helm.ai

Technology

StaffSoftwareEngineer

$150–250k United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Staff Software Engineer at Helm.ai. Skills: ML infrastructure, Distributed systems, Cloud platforms. Architect ML infrastructure. Design ML infrastructure”

Industry & Context.

Technology
Problems you'll solve

Problem solver; Tackle complex technical challenges; Root cause analysis

What They're Looking For.

Must Have

Building and scaling cloud-based infrastructure, Expert knowledge of distributed systems, Expert knowledge of cloud platforms, Expert knowledge of Kubernetes, Expert knowledge of Docker, Expert knowledge of microservices architecture, Deep experience building large scale services, Solid background in machine learning concepts, Leadership and collaboration skills, Experience working in agile development, Mentoring high-performing teams, Ability to manage ambiguity, Thrive in fast-paced environment, Passionate problem solver, Focus on building practical systems, Focus on building reliable systems, Focus on building efficient systems, Systems that scale in production

Nice to Have

AWS experience, GCP experience, Azure experience, Model training experience, Model validation experience

What You'll Do.

Architect ML infrastructure

Design ML infrastructure

Build ML infrastructure

Process large-scale data

Develop machine learning models

Optimize platform implementation

Build user-centric systems

Take ownership of platform lifecycle

Design platform lifecycle

Implement platform lifecycle

Deploy platform lifecycle

Monitor platform lifecycle

Work with cross-functional teams

Incorporate cutting-edge technologies

Tackle complex technical challenges

Optimize infrastructure

Provide solutions for data processing

Provide solutions for data storage

Provide solutions for data access

Foster culture of excellence

Foster high-performance culture

How You'll Work.

Team & Collaboration

Cross-functional teams; Data science teams; Product teams; Operations teams

Process & Methodology

Agile development

Full Job Description

We help make autonomous technologies more efficient, safer, and accessible. Helm.ai http://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 http://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: - 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 intern

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