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NEXTMOVEFDE careers · United States

Lead Software Engineer, Data Platform

No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.

Technologies

Go · Python · Svelte · GKE · TensorFlow · TFLite · ONNX · MongoDB Atlas · GCP · Azure

About Viam

Software platform to configure, control, and manage physical devices and fleets of machines, built so developers can program hardware like software.

Series C · 50–100 people

Job description

The full responsibilities and requirements are on the employer’s site.

Read the job description
Source and classification

Internal deployment & tooling · Evidence for this classification:

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 moves data from devices to the cloud and makes it usable across the Viam platform. On top of that foundation, the team also owns the ML infrastructure that turns that data into models: training workflows, labeling pipelines, and inference in both cloud and at the edge. The team works in Go and Python with a Svelte frontend, running ML workloads on GKE using TensorFlow, TFLite, and ONNX, with MongoDB Atlas, GCP, and Azure for the data layer. You will report 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 5+ engineers: set direction, run planning,
More from the job description

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. The Engineering Challenge Building software for machines introduces challenges that traditional software systems rarely face. Devices operate in real-world environments, networks are unreliable, and software must interact with hardware, sensors, and real-time data. At Viam, engineers build the platform and tools that make those machines programmable, observable, and manageable at scale. 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 moves data from devices to the cloud and makes it usable across the Viam platform. On top of that foundation, the team also owns the ML infrastructure that turns that data into models: training workflows, labeling pipelines, and inference in both cloud and at the edge. The team works in Go and Python with a Svelte [... source excerpt omitted ...] with MongoDB Atlas, GCP, and Azure for the data layer. You will report 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 5+ 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 th [... source excerpt omitted ...] Ideally you have: Led engineering teams through hiring, coaching, performance management, and career development Built and scaled backend, platform, or infrastructure systems in production Shipped products across APIs, backend services, and user interfaces Made sound architectural decisions and navigated tradeoffs around scale, reliability, and performance Influenced product and technical direction through strong judgment and execution Drove cross-functional projects from ambiguity to production Worked on distributed systems, data-intensive systems, streaming pipelines, platform infrastructure, or ML infrastructure **Experience with robotics or IoT is not required. How We

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