What are the responsibilities and job description for the Staff Backend Engineer - AI position at Career Renew?
We build autonomous manufacturing systems powered by AI and robotics to solve America's manufacturing workforce crisis. We're creating the intelligence layer that lets machines run autonomously so manufacturers can scale production without scaling headcount.
You'll join a small in-person team in NYC with deep experience from defense tech and AI who've already shipped products to DoD customers. This is your chance to build the future of American manufacturing at the intersection of ML robotics and distributed systems.
As Staff ML Backend Engineer you'll own the entire data pipeline for robotics sensor data and build foundational ML infrastructure. You'll make key technical decisions around storage processing and analytics while functioning as a research engineer to keep ML team iteration cycles fast.
This Staff Backend Engineer will build the foundational infrastructure for our machine learning pipelines, focusing on creating robust, scalable backend systems for advanced robotics. The role involves owning 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 a generalist software engineering role focused on the backend, particularly on building production systems for large-scale data and data pipelines, rather than internal tooling.
Tech stack
Python, Rust, C , Distributed Systems, Data Pipelines, PyTorch, TensorFlow, Time-series Databases, GPU
Requirements:
7 years of experience in backend engineering building production data pipelines in Python, Rust, or C (Mandatory)
Built production data pipelines for large-scale sensor/video data. (Mandatory)
Experience with distributed systems handling low-latency, high-throughput data flows (Mandatory)
Experience in latency-sensitive environments (e.g. trading systems, real-time industrial/robotics systems) (Nice-to-have)
BS/MS in Computer Science or a related technical field. (Mandatory)
Strong proficiency in Python, Rust, or C for backend / systems development (Mandatory)
Experience with time-series or streaming data systems (e.g. sensor data pipelines, event streams) (Mandatory)
Familiarity with ML infrastructure or supporting ML pipelines in production (not just model training) (Nice-to-have)