Point One Navigation
Staff Computer Vision Engineer
New
215270 –265800 USD / yearUSALeadRemotecomputer visionimage processingalgorithm designsoftware architecture
Lead the lifecycle of spatial AI and visual navigation features, from camera integration to algorithmic design, enabling precision location solutions on various devices.
Responsibilities
- State-of-the-art CV and SLAM techniques are successfully translated from research papers, internal prototypes, or third-party solutions into highly performant, production-grade algorithms.
- Rigorous benchmarking pipelines are established to objectively evaluate internal algorithms against commercial OTS solutions and vendor offerings.
- Vision pipelines automatically generate and maintain accurate, semantically rich maps of complex indoor environments with minimal manual intervention.
- Real-time localization and multi-agent tracking (assets, robots, people) are highly robust, minimizing latency and identity switches even in dynamic or visually degraded conditions.
- Spatial data, coordinate frames, and map layers are exposed via clean data models and APIs, empowering our UI and infrastructure teams to build seamless user-facing applications.
- Junior engineers grow faster and the team's practices improve measurably over time.
Requirements
- 7+ years of professional algorithm and software development experience, with significant depth in applied research, computer vision, or robotics.
- Expertise in modern C++ (C++14 or later) and Python, with a demonstrated history of success of taking AI model prototypes (PyTorch, TensorFlow) and turning them into scalable, real-time production systems.
- Expertise in ROS1/ROS2.
- Hands-on experience with Visual SLAM, 3D reconstruction, and mapping architectures.
- Experience in deploying semantic segmentation/object detection in real-world environments.
- Experience with multi-view geometry, camera calibration, and fusing vision with other sensor modalities (IMU, GNSS).
- Ability to take high-level research and business goals and decompose them into actionable engineering tasks, realistic schedules, and clear milestones.
- MS or PhD in Computer Science, Robotics, or equivalent experience.
- Bonus Points For
- Background in deploying optimized vision models to edge devices using TensorRT, ONNX, or platform-specific accelerators.
- Experience in deploying multi-object tracking and ReID architectures in real-world, dynamic environments.
- Familiarity with managing large-scale point clouds, mesh generation, or NeRFs/Gaussian Splatting for environmental representation.
Other
- Point One Navigation is on a mission to bridge the digital and physical worlds through precision location, with an API-first, developer-focused approach. Our RTK corrections network and FusionEngine™ software deliver centimeter-level accuracy and high-confidence positioning for vehicles, robots, drones, and devices across industries in outdoor applications. We are actively broadening our expertise into indoor environments to provide the same high-standard localization and navigational quality for users everywhere.
- Staff Computer Vision Engineers are responsible for the comprehensive lifecycle of Point One’s spatial AI and visual navigation features, overseeing everything from initial camera integration and image processing to high-level architectural and algorithmic design.
- This is an ownership-first role: you will conceptualize and drive complex technical challenges end-to-end - from early architecture through deployment in mission-critical systems - while raising the technical bar across the team.
- FusionEngine already powers a wide range of devices, hardware platforms, and customer applications. The R&D team is responsible for making sure our vision and perception systems work reliably across all of them: Designing solutions robust to visually challenging environments, optimizing models for compute-constrained edge devices, and ensuring our algorithms stay thoroughly tested, verified, and production-ready as we scale.
- Applied Research, Benchmarking & Selection
- Lead the research, evaluation, and selection of state-of-the-art computer vision, deep learning, and spatial navigation methodologies for highly accurate 3D maps of large-scale facilities, considering both internal development and third-party commercial solutions.
- Develop or integrate deep learning and classical CV algorithms to extract semantic information from environments (e.g., structural elements, zones, and specific objects) for overlay onto base map.
- Ensure maps can be dynamically updated over time as the physical layout of a facility changes, enabling map version management and consistency.
- Design and own a rigorous benchmarking framework to continuously evaluate the accuracy, latency, compute footprint, and reliability of internal code versus off-the-shelf and vendor technologies.
- Rapidly prototype new perception capabilities and architect their transition into highly optimized, edge-capable production code, or seamlessly encapsulate and integrate verified third-party modules.
- Collaborate tightly with infrastructure and UI engineers to manage data products, render maps, and track assets for the end user.
- Drive Real-Time Localization and Tracking
- Understand how and work with the larger navigation team to use camera data with GNSS, IMU, wheel odometry, and other indoor positioning signals to maintain high-confidence state estimation for moving agents in all environments.
- Drive performance tuning for edge deployment to ensure tracking algorithms run with low latency and high reliability on constrained compute architectures.
- Proactively identify failure modes in tracking and mapping and design robust algorithmic fallbacks.
- Raise the Technical Bar
- Mentor junior engineers and establish best practices across the team.
- Contribute to architecture discussions, technical strategy, and roadmap planning.
- At Point One, our cultural and operating design is built around one guiding principle: we must move with extreme speed and efficiency of effort to stay in a leadership position.
- This environment gives people a high level of autonomy and the ability to make a real impact . It also challenges every team member to grow — both professionally and personally. Because we focus on promoting from within rather than relying on external hiring, the opportunities for advancement are tremendous for those who seek them.
- That said, growth only comes from delivering in the present. What matters most is the job to be done today , not the job you want tomorrow. When we all focus on today’s outcomes with excellence, the path to greater responsibility and growth naturally follows.
- We think about our culture in two dimensions:
- These are the behaviors we expect every team member to bring to work — the foundation of being a consummate, high-output teammate:
- Trust / Assume Best Intent — Trust allows us to move fast. When we start from trust, we spend no time second-guessing or looking for ulterior motives and thus focus all our energy on acting.
- High Output, Action Oriented — Our default posture is “yes.” We bias toward action and deliver results quickly, knowing that speed and efficiency compound into impact as we unblock others around us.
- Divine Discontent — We’re never satisfied with the status quo and are self-motivated to improve ourselves, our work, and our company. We actively seek feedback in real-time to shorten improvement cycles.
- No Ego, One Team — Collaboration without ego creates leverage. When we win as one team, we eliminate friction and move faster together.
- Self Accountability — Taking ownership is the straightest line to learning, self-improvement, and correcting our course of action. And blaming others around us is a fast path to destroying trust.
- These are the systems and norms that amplify speed and efficiency at the company level:
- Edge Innovation — We bias toward action over approval. Experiment, decide, and move — failure is just a step toward faster learning.
- No Hierarchies — We practice self-prioritization and go direct to the source. Flattening layers reduces drag and maximizes autonomy.
- Customer Experience First — We optimize for the end-to-end customer outcome, not functional or departmental efficiency. This focus cuts waste, aligns priorities, and ensures we spend effort where it matters most.
- If this role sounds like a fit, we’d love to hear from you. Apply below and join us in shaping the future of precise location.