Lead Software Engineer, Data Platform

About the role

About Viam

Founded by Eliot Horowitz, co-founder and former CTO of MongoDB, Viam is a novel robotics engineering platform that lets you configure, control, and manage robots intuitively and quickly. We’re inspiring a generation of engineers to solve complicated automation problems with our uniquely powerful suite of software tools.

We’re a ~100-person company headquartered in New York City.

About the Role

New York City (Hybrid 3+ days per week in office)

We are looking for a hands-on engineering manager to lead our Data/ML team. The role is responsible for developing engineers, driving execution, and making architectural decisions.

The Data/ML team owns the infrastructure that takes data from robotics deployments, whether that's physical hardware workcells or simulation, and moves it to the cloud for use across the Viam platform. On top of that foundation, the team also owns the ML workflows to turn that data into models for physical AI: organizing the large data ingestion into training datasets, labeling pipelines and VLA episode capture, model training, inference both in the cloud and at the edge, and model evaluation.

The team works in Go and Python with a Svelte frontend, running multi-region Go services on GKE. On the ML side, we support a range of frameworks and runtimes, including TensorFlow, TFLite, ONNX, and OpenVINO, and serve models such as OpenVLA and NVIDIA Cosmos, with new models evaluated continuously. Our data layer spans MongoDB Atlas, ClickHouse, GCS, and Azure Blob Storage.

This role reports to the VP of Engineering.

What You'll Own

Lead Engineers at Viam own problems from product design through production and play an active role in shaping how the platform evolves.

- Lead and develop a team of 3+ engineers: set direction, run planning, ship reliably, and grow the team through coaching, feedback, and performance conversations

- Write code and ship features alongside your team across the full stack, from backend infrastructure through UI

- Own the architecture of the data pipeline end to end, from device to cloud, including storage, querying, and the APIs that power the rest of the platform

- Drive the reliability and performance of high-volume data ingestion, ML training, and inference infrastructure, from custom training workflows to the services that power auto-labeling and model evaluation

- Have opinions on what gets built and how users experience it, and bring those into product decisions early

- Own cross-team initiatives through to resolution, working closely with Computer Vision, Fleet Management, Mobile, and Solutions Engineering

What You Bring

We are looking for an experienced engineering manager who remains deeply technical, can develop engineers, and is comfortable setting direction while staying close to the code. Ideally you have:

- Built and scaled backend, platform, or infrastructure systems in production