Software Engineer, Backend

Backend Engineer

Location

New York City

Employment Type

Full time

Location Type

On-site

Department

Engineering

Overview

Application

About Us

Nidus is building autonomous manufacturing systems powered by AI and robotics. U.S. manufacturing faces a structural challenge: a shrinking skilled workforce, underutilized equipment, and supply chains that can't keep pace with demand. We believe the answer isn't more people — it's smarter systems. We're building the intelligence layer that lets machines run autonomously, so manufacturers can scale production without scaling headcount.

Our team comes from the intersection of defense technology and AI. We've built and shipped products to DoD customers, and we bring deep experience across ML, robotics, product development, and defense

We're a small, in-person team in New York City working on hard problems that matter. If you want to build the future of American manufacturing, we'd love to hear from you.

Role Overview

We are seeking a Staff ML Backend Engineer to join our team and build the foundational infrastructure that powers our machine learning pipelines for advanced robotics systems. This role will focus on creating robust, scalable backend systems that enable our ML and robotics teams to train, deploy, and monitor models in production manufacturing environments. You'll be working at the intersection of distributed systems, ML infrastructure, and robotics sensor data collection

Key Responsibilities

• Owning the data collection/storage pipeline for our robotics sensor data
• Making technical decisions around efficient storage and processing of that sensor data
• Building software for analytics, monitoring, and visualization of the data, and making key decisions on when we should build vs buy
• Function as a research engineer for our ML team - building out tooling and infra as needed to keep their iteration cycles fast

Required Qualifications

• 7+ years of experience in backend engineering, with demonstrated expertise in building scalable distributed systems
• Strong proficiency in Python, Rust, or C++
• Experience building ML infrastructure for video and sensor data
• Experience with time series databases or other storage techniques for sensor data
• Strong grasp of system design principles, API design, and performance optimization techniques

Preferred Qualifications

• Experience with robotics systems, real-time data processing, or edge computing environments
• Familiarity with ML frameworks (PyTorch, TensorFlow) and model serving platforms (TorchServe, TensorFlow Serving, NVIDIA Triton)
• Background in manufacturing systems, industrial automation, or hardware-software integration
• Experience with high-frequency data streaming and time-series databases
• Track record of building systems that support continuous deployment in production environments
• Understanding of GPU infrastructure and optimization for ML workloads