Staff Backend Engineer – AI & Robotics Infrastructure

About the Company

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

The Role

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

Tech Stack

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.

Who You Are

Must-Haves

• 7–10 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)

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

Compensation

$200,000 – $230,000 + Equity

Ability to work on-site in New York City (5 days/week)