Member of Technical Staff, Infrastructure

Location

San Francisco, CA

On-site role requiring 6 days/week in the San Francisco office.

Compensation

$200,000 – $350,000 Base + Competitive Equity

Visa

Open to H-1B Transfers / OPT Transfers
No new visa sponsorship.

Company Stage

Series A – Growth-Stage AI / Robotics Technology Company

Industry

Artificial Intelligence, Robotics, Machine Learning, Infrastructure, Distributed Systems, Autonomous Systems, Cloud Computing, ML Infrastructure

About the Company

Our client is building general-purpose autonomous robots designed to automate physical labor in real-world industrial environments.

The company is developing the infrastructure required to train, deploy, and continuously improve AI models powering a fleet of physically deployed robots.

The company has raised approximately $23M from leading investors and has assembled a highly technical team with backgrounds across leading AI, robotics, infrastructure, and technology companies.

As a Member of Technical Staff, Infrastructure, you'll work on foundational systems spanning distributed computing, large-scale data pipelines, GPU infrastructure, model training, networking, deployment, and real-time robot operations.

This is an opportunity for a high-slope systems engineer who wants broad ownership in an early-stage environment where infrastructure decisions have immediate impact and engineering standards are still being established.

What You'll Do

• Build and own distributed systems infrastructure powering a fleet of deployed autonomous robots
• Design infrastructure for large-scale model training and inference workloads
• Build training orchestration systems for large-scale ML workloads
• Design compute scheduling and resource allocation systems
• Build fault-tolerant infrastructure for production AI and robotics workloads
• Develop networking infrastructure supporting physically deployed robots
• Design and maintain large-scale data pipelines for robot telemetry and video data
• Build systems capable of ingesting and processing petabyte-scale datasets
• Ensure training infrastructure can continuously ingest and process production robot data
• Architect continuous-learning infrastructure connecting deployed robots to model training systems
• Build reliable pipelines that move production trajectories from robots back into training
• Optimize data infrastructure to keep GPU workloads continuously supplied with data
• Build and improve GPU cluster orchestration and compute infrastructure
• Work on low-latency infrastructure supporting robot operations across long distances
• Design systems capable of meeting demanding latency and reliability requirements
• Build internal infrastructure and developer tooling that improves engineering velocity
• Identify infrastructure bottlenecks and own solutions end-to-end
• Work across different areas of the stack depending on the highest-leverage technical problem
• Develop core libraries and infrastructure components used across the engineering organization
• Improve observability, reliability, and operational tooling across distributed systems
• Establish engineering standards and best practices across infrastructure
• Work closely with ML researchers, robotics engineers, and software engineers
• Support infrastructure powering large-scale model training and experimentation
• Build systems that can reliably operate in real-world production environments
• Make architectural decisions in a rapidly evolving technical environment
• Operate with significant autonomy and ownership
• Move quickly from identifying a bottleneck to designing and shipping a solution
• Help shape the company's long-term infrastructure and distributed systems architecture

Ideal Candidate Background

Experience Requirements

• 2+ years of experience in infrastructure, distributed systems, or related engineering roles
• Strong systems engineering background
• Experience building production infrastructure or distributed systems
• Experience working with large-scale data, compute, or infrastructure systems
• Experience at a highly technical, tier-1 VC-backed startup, technology company, or research lab
• Experience operating in environments with a high engineering talent bar
• Experience owning technical projects end-to-end
• Experience working in fast-moving startup or research environments
• Strong ability to operate independently with minimal structure
• Strong engineering judgment and problem-solving ability
• Ability to move quickly between different technical problem areas
• Strong communication skills and technical curiosity
• Comfortable working on-site in San Francisco 6 days/week
• Comfortable working long hours in a highly demanding startup environment

Technical Requirements

• Strong distributed systems fundamentals
• Strong systems engineering fundamentals
• Experience building scalable infrastructure
• Experience with large-scale data pipelines
• Experience with cloud infrastructure and distributed compute
• Experience with GPU or high-performance computing infrastructure preferred
• Experience with ML infrastructure or model training systems preferred
• Experience with compute scheduling or orchestration preferred
• Experience with fault-tolerant distributed systems
• Experience with networking and infrastructure systems
• Experience with large-scale data processing
• Strong Python programming skills
• Strong C/C++ programming skills or experience preferred
• Experience working with production infrastructure
• Strong understanding of system design and architecture
• Ability to troubleshoot complex distributed systems
• Ability to reason about performance, reliability, and scalability
• Experience with large-scale training infrastructure preferred
• Experience with petabyte-scale data systems preferred
• Experience with multi-node training orchestration preferred
• Experience with real-time or low-latency systems preferred
• Experience with robotics or autonomous systems preferred

Education

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or related technical field preferred
• Strong computer science and systems fundamentals
• Equivalent practical engineering experience accepted

Soft Skills

• Exceptional ownership and execution ability
• High technical slope and learning velocity
• Strong engineering intuition
• Highly hands-on engineering mindset
• Comfortable operating with significant autonomy
• Strong problem-solving ability
• Strong technical communication skills
• High energy and urgency
• Comfortable working in highly demanding startup environments
• Comfortable working across different technical domains
• Strong builder mentality
• Comfortable operating without established processes
• Strong attention to engineering quality
• Willing to tackle whichever technical bottleneck is most important
• Comfortable making decisions with incomplete information
• Strong collaboration skills
• Comfortable working closely with highly technical engineers and researchers
• Low-ego technical working style
• Strong interest in AI, robotics, infrastructure, and distributed systems
• Comfortable working 6 days/week onsite in San Francisco

Compensation & Benefits

• Base Salary: $200,000 – $350,000
• Competitive startup equity
• Potential flexibility toward the top end of the range for exceptional candidates
• Opportunity to join a highly technical early-stage AI and robotics company
• Ownership over foundational infrastructure systems
• Exposure to petabyte-scale data infrastructure
• Opportunity to build GPU and ML training infrastructure
• Work on distributed systems powering physically deployed autonomous robots
• Opportunity to solve difficult real-world infrastructure and systems problems
• Direct impact on production robotics systems
• High technical ownership and autonomy
• Opportunity to work closely with experienced AI, robotics, and infrastructure engineers
• Opportunity to shape engineering standards and infrastructure architecture from an early stage
• H-1B and OPT transfer support

Why Join

This is an opportunity to join an ambitious AI and robotics company building infrastructure for autonomous systems operating in the physical world.

You'll work on infrastructure problems that span distributed systems, petabyte-scale data pipelines, GPU clusters, model training, networking, and real-time robot deployment.

Unlike mature infrastructure organizations where responsibilities are highly specialized, this role gives you the opportunity to move wherever the highest-leverage bottleneck exists and own solutions end-to-end.

If you enjoy difficult systems problems, high technical ownership, rapid execution, and building infrastructure from the ground up, this role offers exceptional scope and technical impact.