Staff Backend Engineer [AI & Robotics Infrastructure]

We’re looking for a Staff Backend Engineer to build the foundational infrastructure for our machine learning pipelines. This is a production-focused role-you’ll own the data collection and storage pipeline for robotics sensor data, making key technical decisions and functioning as a research engineer for the ML team to accelerate their iteration cycles.

This is NOT:

• An internal tooling role
• A traditional data engineering position (ETL, warehousing, BI)
• A web development or full-stack role
• A DevOps or platform engineering position

This IS:

• A deep backend engineering role building production systems for large-scale data
• Ownership of the entire sensor/video data pipeline
• Direct collaboration with ML researchers to understand and solve their infrastructure needs
• Real architectural decision-making with long-term impact

What You’ll Do

• Own the data pipeline: Design, build, and maintain the infrastructure that ingests, stores, and processes high-volume sensor and video data from robotic systems
• Enable ML iteration: Build tooling and infrastructure that allows the ML team to train, evaluate, and deploy models faster
• Make architectural decisions: Evaluate build-vs-buy tradeoffs, design storage and processing systems, and ensure scalability and reliability
• Work with physical systems: Build software that directly interfaces with real hardware-not just simulation
• Optimize for performance: Build low-latency, high-throughput distributed systems that can handle real-time data flows

• Primary Languages: Python, Rust, or C++
• Data Infrastructure: Distributed systems, streaming data pipelines, time-series databases
• ML Tools: PyTorch, TensorFlow, GPU infrastructure
• Environment: On-premise and cloud hybrid
• We don’t expect you to know everything-but you should be deeply proficient in at least one of Python/Rust/C++ and have experience building data-intensive backend systems.

Must-Haves

• 4-10 years of backend engineering experience building production data pipelines
• Strong proficiency in Python, Rust, or C++ for backend/systems development
• Experience building large-scale sensor or video data pipelines
• Experience with distributed systems handling low-latency, high-throughput data flows
• Background in latency-sensitive environments (e.g., trading systems, real-time industrial systems, robotics, autonomous vehicles)
• US Citizenship (required for regulatory compliance)
• Ability to work on-site in New York City (5 days/week)

Nice-to-Haves

• Experience with robotics systems, autonomous vehicles, or industrial automation
• Familiarity with ML infrastructure (feature stores, model serving, data versioning)
• Background in manufacturing, defense tech, or hardware-software integration
• Experience with GPU infrastructure and performance optimization for ML workloads
• MS/PhD in Computer Science or a related technical field

Traits We’re NOT Looking For

• Pure web development background (React, Node, full-stack)
• Experience limited to internal tooling or traditional data engineering (ETL, data warehousing)
• Systems integration or DevOps-focused backgrounds
• Short-tenured job history (< 2 years per role), * Master’s (Preferred)

Impact: Your code will run on physical systems that manufacture real products-not just move pixels on a screen

Ownership: You’ll shape the architecture from day one in a small, high-agency team

Mission: Work on strengthening domestic manufacturing and industrial resilience

Compensation: Competitive salary ($180K-$230K) + meaningful equity

Team: Work alongside world-class engineers and researchers with deep domain expertise

Note: We are unable to sponsor visas for this position. US Citizenship is required.

Pay: $180,000.00 - $230,000.00 per year

Application Question(s):

• Briefly describe a project where you built backend software that directly interfaced with physical hardware, sensors, or robotic systems. (If none, write “N/A”)

• Describe your experience with Rust or C++ for performance-critical systems. (If none, write “N/A”)

• Describe a system you built that processed high-volume data with strict latency requirements. (Include latency targets and scale if possible.)

• What draws you to building software for physical systems like robotics and manufacturing?

We’re a well-funded, early-stage technology company building the next generation of autonomous physical systems. Our mission is to solve critical bottlenecks in industrial production by creating an intelligence layer that enables machines to operate continuously and autonomously.

We combine robotics with cutting-edge machine learning approaches-including vision-language-action models-to transform how physical production systems run. Our goal is to make manufacturing more efficient, scalable, and resilient in environments where skilled labor is constrained.

What makes us different:

Small, elite, in-person team with deep experience in AI, robotics, and industrial systems

Already shipping products to customers in regulated industries

Backed by top-tier investors with a clear path to scale