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Computer Vision Slam Engineer Jobs (NOW HIRING)

Quidient

SLAM Engineer

Columbia, MD

$175K - $230K/yr

Overview Quidient is hiring a SLAM Engineer to advance the on-device visual-inertial SLAM system ... Master's, or PhD in Computer Science, Computer Vision, Robotics, or a related field - or equivalent ...

Quidient

SLAM Engineer

Columbia, MD · On-site

$175K - $230K/yr

Overview Quidient is hiring a SLAM Engineer to advance the on-device visual-inertial SLAM system ... Master's, or PhD in Computer Science, Computer Vision, Robotics, or a related field - or equivalent ...

Quid, Inc.

SLAM Engineer

Columbia, MD · On-site

$175K - $230K/yr

Overview Quidient is hiring a SLAM Engineer to advance the on‑device visual‑inertial SLAM ... Master's, or PhD in Computer Science, Computer Vision, Robotics, or a related field -- or ...

Sunday Inc

SLAM Engineer

Redwood City, CA · On-site

As a SLAM Engineer, your work will be essential in enabling our home robot to navigate safely in ... Experience with vision-only or lidar-based SLAM pipelines * Deep understanding of spatial math ...

1872 Consulting

Computer Vision Engineer

Chicago, IL · On-site

$115K - $135K/yr

They are seeking a Computer Vision Engineer to develop and implement innovative computer vision ... SLAM etc) • Hands-on experience applying machine learning and deep learning to vision data ...

Meta

Computer Vision Engineer

Sunnyvale, CA

$121K/yr

... SLAM, scene reconstruction, machine perception, visualization, and human interaction. Computer ... Vision Engineer Responsibilities: * Design and develop novel calibration algorithms for sensors and ...

Meta

Computer Vision Engineer

Burlingame, CA

$121K/yr

... SLAM, scene reconstruction, machine perception, visualization, and human interaction. Computer ... Vision Engineer Responsibilities: * Design and develop novel calibration algorithms for sensors and ...

Nexxa.ai

AI Vision Engineer

San Francisco, CA · On-site

What You'll Do * Design, train, evaluate, and deploy computer vision models for real-world ... Familiarity with 3D vision, SLAM, or sensor fusion (e.g., camera + LiDAR) for industrial or ...

Nexxa.AI

AI Vision Engineer

San Francisco, CA · On-site

What You'll Do * Design, train, evaluate, and deploy computer vision models for real-world ... Familiarity with 3D vision, SLAM, or sensor fusion (e.g., camera + LiDAR) for industrial or ...

Lyte

Senior Camera & Vision Engineer

Sunnyvale, CA · On-site

$150K - $300K/yr

Develop and integrate computer vision and ML-based algorithms into the perception stack * Work with ... Background in depth estimation, stereo vision, SLAM, or visual-inertial systems * Experience with ...

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Computer Vision Slam Engineer information

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$48.5K

$121.5K

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How much do computer vision slam engineer jobs pay per year?

As of Sep 12, 2026, the average yearly pay for computer vision slam engineer in the United States is $121,515.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $131,500.00 per year, depending on experience, location, and employer.

What states have the most Computer Vision Slam Engineer jobs?

States with the most job openings for Computer Vision Slam Engineer jobs include:

What are popular job titles related to Computer Vision Slam Engineer jobs?

For Computer Vision Slam Engineer jobs, the most frequently searched job titles are:

Infographic showing various Computer Vision Slam Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 15% Part Time, and 6% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $121,515 per year, or $58.4 per hour.

SLAM Engineer

Columbia, MD

Quidient
Software Development • 11 - 50 employees
Learn more about Quidientexternal

$175K - $230K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 25 days ago

Job description

Overview

Quidient is hiring a SLAM Engineer to advance the on-device visual-inertial SLAM system that powers our mobile capture experience. This role is central to how everyday users capture the world using their phones. You will enhance the live tracking pipeline running on mobile, pushing the limits of accuracy, robustness, and real-time AR visualization across a wide range of real-world scenarios - going well beyond what platform-provided solutions can deliver.

This is a hybrid position, meaning that you will need to live within easy driving distance to our Technology Center in Columbia, Maryland.

What You'll DoReal-time SLAM & Sensor Fusion
  • Develop and advance our on-device visual-inertial odometry and VI-SLAM pipeline - including sensor fusion across multi-camera streams, IMU, and depth - with drift correction and relocalization for production capture workflows.
  • Improve robustness across the full range of real-world user behavior - low-light, fast motion, textureless environments, and difficult geometry.
  • Drive down latency and memory footprint on mobile hardware, offloading compute to GPU where possible. Direct experience with GPU programming (Metal shaders, CUDA kernels, or equivalent) is a strong advantage.
  • Develop and extend calibration pipelines covering camera intrinsics, extrinsics, IMU biases, and time synchronization across multi-sensor mobile configurations.
Research Integration & Evaluation
  • Collaborate with the team's deep learning expertise to evaluate and selectively integrate learning-based methods alongside classical components in the live tracking stack.
  • Build and extend evaluation methodology grounded in real user captures.
  • Translate research progress into shipped capability in a fast-moving environment.
What You BringMust-Have Qualifications:
  • Master's, or PhD in Computer Science, Computer Vision, Robotics, or a related field - or equivalent demonstrated experience.
  • Significant hands-on experience developing or substantially improving a real-time visual-inertial odometry or VI-SLAM system, with a strong emphasis on camera-based pipelines.
  • Strong C++ (modern, performance-aware) and Python (tooling, prototyping, ML work).
  • Deep working knowledge of multiview geometry, nonlinear estimation, inertial sensing, and the practical failure modes of real-time tracking on resource-constrained devices.
  • Real experience with sensor calibration on real hardware.
  • Ability to read the deep learning literature critically and openness to integrating learned components over time.
  • 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 with mobile SLAM or VIO on iOS or Android (iPhone strongly preferred). Familiarity with constrained-system development including ARM, threading, memory profiling, and power-aware design.
  • Direct GPU programming experience - Metal shaders, CUDA kernels, or GPU compute APIs - for offloading SLAM or vision workloads on mobile hardware.
  • Experience with multi-camera and multi-sensor fusion (RGB, depth, IMU) in a mobile or embedded context.
  • Track record of shipping SLAM or visual odometry systems in production on mobile or embedded platforms.
  • Contributor to open-source SLAM or VIO projects (OpenVINS, ORB-SLAM, VINS-Mono, or similar).
What We OfferCompensation:
  • Salary Range: $175,000 - $230,000.
  • 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.

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