Senior or Staff Computer Vision Engineer

Responsibilities

• Design, prototype, evaluate, and productionize advanced computer vision and deep learning systems for 3D reconstruction, scene understanding, semantic modeling, and structured property representation
• Work across the full lifecycle of applied research and engineering: identifying relevant academic and industry approaches, writing project plans and technical specs, building proof-of-concepts, training and evaluating models, analyzing reconstruction quality and performance, and integrating successful approaches into production systems
• Partner closely with 3D reconstruction, Product, Design, Engineering, modeling, infrastructure, graphics, frontend, and backend teams to turn ambiguous technical and customer needs into clearly scoped experiments and production capabilities
• Work may include: mobile capture, aerial imagery, multimodal sensor fusion, multi-view reconstruction, pose estimation, feature matching, dense geometry, model fitting, semantic understanding, volumetric/surfel/surface-based representations, CAD-quality structured outputs, Gaussian Splatting, VLMs, or foundation-model-style approaches for correspondence and 3D understanding

Requirements

• 5+ years of experience in computer vision, machine learning, or 3D reconstruction within academic research and/or industry environments
• Hands-on experience with one or more areas of modern 3D vision and reconstruction (multi-view geometry, pose estimation, camera calibration, structure-from-motion, feature matching, dense reconstruction, structured 3D reconstruction, model fitting, optimization, scene understanding, semantic modeling, or structured 3D representation)
• Practical deep learning experience applied to 3D reconstruction, geometry, correspondence, pose, segmentation, semantic understanding, VLMs, or related spatial ML problems
• Strong software engineering skills in Python and/or C++
• Ability to prototype quickly, train models, evaluate approaches rigorously, and translate promising research into practical systems
• Experience designing experiments with clear metrics, baselines, datasets, evaluation plans, and go/no-go criteria
• Ability to write clear project plans, technical specs, research summaries, experiment reports, and production-readiness documentation
• Track record of technical ownership and the ability to independently drive projects from ambiguity through implementation and delivery
• Strong collaboration skills working with researchers, engineers, 3D modelers, infrastructure teams, product partners, and cross-functional stakeholders
• Strong product and engineering judgment balancing technical ambition, customer value, production constraints, scalability, reliability, timing, and business impact
• Master's or PhD in Computer Science, Machine Learning, Computer Vision, Robotics, Graphics, or a related field

Staff-Level Additional Requirements

• Experience building and shipping production CV, ML, or 3D reconstruction systems at scale
• Ability to define technical direction, architectural strategy, evaluation methodology, and quality/performance standards for complex CV or ML systems
• Proven ability to lead initiatives from early-stage research and experimentation through production deployment, monitoring, and long-term system ownership
• Ability to operate effectively in ambiguous problem spaces and drive alignment across cross-functional stakeholders
• Strong communication and influence skills translating complex technical concepts for both technical and non-technical audiences
• Experience mentoring engineers and raising the technical bar through architecture reviews, technical leadership, experimentation frameworks, and engineering best practices
• Track record of translating research or technical innovation into measurable product, customer, or business impact