Top Tech Jobs & Startup Jobs

Train and evaluate PyTorch computer vision models for visual localization, including feature matching, image retrieval, pose regression, and scene-coordinate regression. Build large-scale image and 3D data pipelines, run experiments on GPU infrastructure, maintain localization benchmarks, and support model export, inference optimization, deployment, and monitoring. Collaborate with research and testing teams to improve production model performance.

Lead engineering for a real-to-sim platform supporting embodied AI and robot learning. Own the technical roadmap and requirements, prototype and ship critical features, benchmark policy transfer, diagnose sim-to-real failures, and evaluate robotics systems in real-world conditions. Collaborate with researchers, product leaders, customers, and test labs while advancing simulation, reinforcement learning, visual perception, and 3D scene representation capabilities.

Build and operate developer-facing products for embodied AI, including APIs, UIs, packages, documentation, backend services, asset workflows, integrations, and asynchronous processing systems. Convert spatial reconstruction and mapping prototypes into production capabilities, support customer simulator and deployment integrations, diagnose reliability issues, and influence the product roadmap. The role requires full-stack product engineering, customer collaboration, and experience with 3D assets or comparable binary formats.

Build and maintain production-grade automation for real-world AI evaluations. The role owns end-to-end workflow orchestration, environment setup, artifact capture, reproducible datasets, scorecards, diagnostics, and release-triggered testing. It also develops agent- and LLM-driven workflows to evaluate customer use cases at scale, converting manual experiments into reliable standing protocols and actionable findings.

Own and characterize a fleet of robotic hardware and capture devices, engineer controlled physical test environments, build instrumentation and ground-truth references, and integrate physical runs into automated evaluation systems. Execute robot bring-up, teleoperation, device-in-the-loop testing, and sim-to-real experiments. Automate calibration, data offload, and condition logging while maintaining safety procedures, fleet operations, documentation, and reproducible test protocols.

Productionize computer vision and 3D reconstruction systems for embodied AI. Own spatial output quality, robustness, evaluation infrastructure, performance, throughput, cost, and reliability. Diagnose real-world failures involving calibration, scale, coordinate frames, and scene complexity. Collaborate with research, product, engineering, and customers to deliver production-ready capabilities, workflows, and interfaces for simulation, training, evaluation, and deployment.

Defines Niantic Spatial’s embodied AI market narrative, positioning, messaging, campaigns, competitive intelligence, pricing and packaging. Translates technical capabilities into customer proof, sales assets, partner content, and adoption strategies. Collaborates with product, engineering, research, business development, robotics OEMs, and strategic customers to establish the company as a leader in physical AI.

Build and manage the go-to-market motion for an Embodied AI product. Responsibilities include mapping the robotics market, generating qualified pipeline, developing customer relationships, qualifying use cases, shaping commercial models, and closing early technical-product deals. The role partners closely with product and company leadership to provide customer insights, establish product-market fit, structure evaluations, negotiate agreements, and support successful handoffs.

As a Senior Computer Vision Engineer, you will design and optimize production-grade systems for visual positioning and 3D mapping, leading technical reviews and collaborating across teams.

Develop inbound and outbound pipeline for spatial computing and AI products. Research prospects, conduct personalized outreach, qualify business and technical needs, explain product value, and create qualified sales conversations. Capture product-market-fit signals, maintain accurate records, coordinate handoffs with business development and sales, and share market feedback with marketing, product, and operations teams.