Senior Computer Vision Engineer

Overview

Quidient is hiring a Senior Computer Vision Engineer to own and operate the computer vision pipelines that power our Generalized Scene Reconstruction Platform. This is a cross-team, cross-product role focused on ensuring CV pipelines are robust, well-integrated, and flowing correctly across every product surface of Quidient Reality®.

This is a full-time hybrid position based in Columbia, Maryland.

What You’ll Do

Computer Vision Pipelines

• Own and maintain end-to-end computer vision pipelines — from image preprocessing and calibration through feature extraction, depth estimation, and segmentation — ensuring data flows correctly across the platform.
• Diagnose and resolve pipeline failures, data quality issues, and integration bugs across CV modules, keeping reconstruction inputs clean and reliable.
• Build monitoring, testing, and validation infrastructure around CV pipelines to catch regressions early and maintain output quality.
• Ensure CV pipelines perform reliably across deployment targets including mobile and autonomous vehicle platforms.

Cross-Team Integration & Tooling

• Work across product and engineering teams to integrate CV outputs into downstream systems — reconstruction, rendering, and platform services.
• Define and maintain interfaces and data contracts between CV modules and the teams that consume them, reducing integration friction.
• Use PyTorch and related frameworks to debug, profile, and maintain ML-based CV components in production.
• Build tooling and scripts that accelerate development workflows across the CV stack.
• Contribute production-quality code in C++ and Python across shared CV infrastructure.
• Collaborate closely with SLAM, SfM, reconstruction, and platform engineering teams to keep the full pipeline healthy and shipping.

What You Bring

Must-Have Qualifications:

• Master’s, or PhD in Computer Science, Computer Vision, Electrical Engineering, or a related field — or equivalent demonstrated experience.
• Hands-on experience building, maintaining, or improving computer vision pipelines in production.
• Solid understanding of core CV concepts: camera models, feature detection/matching, depth estimation, image segmentation, and multi-view geometry.
• Proficiency with PyTorch or a comparable ML framework, applied to computer vision problems.
• A pipeline-first mindset — you care about data flow, error handling, testing, and operational reliability as much as algorithmic novelty.
• Strong C++ and Python skills in a production or research codebase context.
• Good judgment about which techniques from the literature translate to production and which do not.
• Must be a U.S. Citizen. This position is not eligible for H-1B Sponsorship.
• Willingness to work on-site in Columbia, MD, in a hybrid capacity.
• Meet Quidient, customer, and government security requirements, which may include, but are not limited to a background check, citizenship verification, and Criminal Justice Information Services verification.

Nice-to-Have Qualifications:

• Experience in fast-paced or startup environments.
• Experience with 3D reconstruction pipelines, including SfM, MVS, or neural scene representations (NeRF, Gaussian Splatting).
• Exposure to mobile CV deployment (ARKit, ARCore, on-device inference) or autonomous vehicle perception stacks.
• Experience with CI/CD, pipeline orchestration, or data validation frameworks in an ML or CV context.
• Familiarity with SLAM, visual-inertial odometry, or sensor fusion systems.
• Publications or open-source contributions in computer vision or 3D reconstruction (CVPR, ICCV, ECCV, or similar venues).

What We Offer

Compensation:

• Salary Range: $160,000 - $210,000
• Annual bonus and equity as appropriate.

Benefits:

• Health insurance
• HSA
• 401(k) with company match
• Life & disability insurance
• Paid holidays & generous PTO
• Opportunities for bonuses, equity, and career growth

Equal Opportunity Employer Statement

Quidient is an Equal Opportunity Employer. Quidient will consider all qualified applicants without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other classification protected by applicable state, federal, or local laws.