Senior or Staff Computer Vision Engineer

5+ years of experience in computer vision, machine learning, or 3D reconstruction within academic research and/or industry environments, with deep domain expertise and a strong track record of solving complex technical problems.

Hands-on experience with one or more areas of modern 3D vision and reconstruction, such as 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, ideally 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.

A track record of technical ownership and the ability to independently drive projects from ambiguity through implementation and delivery.

Strong collaboration skills and comfort working with researchers, engineers, 3D modelers, infrastructure teams, product partners, and other cross-functional stakeholders.

Strong product and engineering judgment, with the ability to balance 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.

For Staff-level candidates, we also look for deeper technical leadership and broader organizational impact, including:

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.

Strong product and engineering judgment, with the ability to balance technical ambition, customer value, scalability, reliability, timing, cost, and business impact.

Ability to operate effectively in ambiguous problem spaces, make pragmatic tradeoff decisions, and drive alignment across cross-functional stakeholders.

Strong communication and influence skills, including the ability to translate complex technical concepts, constraints, and tradeoffs 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, experimentation, or technical innovation into measurable product, customer, or business impact.

Nice to haves

Research or industry experience in modern reconstruction and spatial AI approaches such as Gaussian Splatting, neural reconstruction, DUSt3R, MASt3R, VGGT, RoMa, surfels, volumetric methods, VLMs, or foundation-model-style approaches for 3D understanding.

Publications or research contributions in relevant venues such as CVPR, ICCV, ECCV, 3DV, ISMAR, SIGGRAPH, NeurIPS, or ICLR.

Experience with large-scale production ML systems, including model serving, monitoring, MLOps, distributed training, scalable data pipelines, and cost/performance optimization.

Familiarity with infrastructure and distributed systems tooling such as GCP, Kubernetes, Ray, or large-scale data processing frameworks.

Experience with geometry processing, graphics, rendering, CAD/BIM workflows, mesh processing, or interactive 3D systems.

Experience with modern deep learning frameworks such as PyTorch or TensorFlow.

Practical experience leveraging AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, or similar tools to accelerate research, prototyping, debugging, and production development.

Hover has Hubs in San Francisco and New York City, where we expect that all employees living within a 50-mile radius of our offices will come into their local Hover office at least three times a week to build rapport and foster organic connection. At this time, Hover is not considering fully remote roles.

The US base salary range for this full-time position is $188,000-$322,000 annually. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all applicable US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. We've posted a range that spans multiple levels within this position to reflect the breadth of candidates we're considering.

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