Senior or Staff Computer Vision Engineer

About the role

We’re expanding Hover’s 3D Reconstruction platform to solve one of our most ambitious technical challenges: transforming real-world sensor data into accurate, structured, CAD-quality models at scale. Computer Vision doesn’t just support Hover’s products, it defines them. We’re looking for either a Senior or Staff Computer Vision Engineer who can turn cutting-edge research into scalable production capabilities while helping shape the future of our reconstruction systems. This role is ideal for someone who wants to own meaningful technical work end to end, move quickly without large-company bureaucracy, and help build accurate digital twin models of the real world at scale.

You’ll work across research, experimentation, and production: reading papers, reproducing and adapting promising academic approaches, training deep learning models, designing rigorous experiments, building proof-of-concepts, and turning successful ideas into robust engineered systems that reach users.

At the Staff level, this role is ideal for a technical leader who is equally comfortable with deep 3D reconstruction work, product strategy, architectural tradeoffs, experiment design, and production deployment. You’ll help connect long-term technical vision, day-to-day engineering execution, and market-driven product needs so Hover’s CV roadmap delivers maximum customer and business impact.

You’ll join a high-performing team of computer vision researchers, reconstruction engineers, graphics specialists, and 3D modelers building systems that turn real-world capture into accurate digital twin models at commercial scale.

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.
• Make practical tradeoffs between research quality, user impact, production constraints, performance, reliability, and cost.
• Work on mobile capture, aerial imagery, multimodal sensor fusion, multi-view reconstruction, pose estimation, feature matching, dense geometry, model fitting, semantic understanding, volumetric, surfel, or surface-based representations, CAD-quality structured outputs, and emerging methods such as Gaussian Splatting, VLMs, or foundation-model-style approaches for correspondence and 3D understanding.
• At the Staff level, shape technical direction across larger initiatives: framing problems, sizing opportunities, prioritizing technical investments, and making “stop / iterate / scale” judgments across reconstruction approaches, model development, data strategy, quality targets, and product impact.
• Communicate technical tradeoffs, resource needs, and roadmap implications to cross-functional partners and leadership.
• Raise the technical bar for the team by setting standards for performance, reliability, maintainability, and cost; leading by example in Python and/or C++; and mentoring engineers through design reviews, architecture discussions, experiment plans, and production-readiness reviews.

Requirements

• 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.
• 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.

Staff-level 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.
• 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.

Benefits

• Competitive salary and meaningful equity in a fast-growing company.
• Comprehensive medical, dental, and vision coverage for you and dependents.
• Unlimited and flexible vacation policy.
• Generous paid parental and new child bonding leave.
• Mandatory Self-Care Days each month to allow employees to recharge.
• Remote wellbeing resources, including recurring fitness classes, meditation/mindfulness tools, virtual therapy, and family planning assistance.
• Support for continued education, including coverage for management training, conferences, workshops, or certifications.

Schedule

Hybrid roles at Hover: 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.

Pay

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 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.