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Computer Vision Engineer Jobs (NOW HIRING)

T3i, Inc.

Computer Vision Engineer - UAS

San Antonio, TX

$100K - $118K/yr

We are seeking a Computer Vision Engineer (CVE) to develop the Blackfoot's perception and visual autonomy stack. This role is critical to delivering robust onboard vision capabilities - object ...

Darbytek

Sr. Computer Vision Engineer

Austin, TX · On-site

$180K - $250K/yr

We are seeking a Full-time Sr Level Computer Vision Engineer to help provide expertise to our team here in Austin TX. Candidates must be local or willing to relocate. Very lucrative opportunity to ...

Meta

Computer Vision Engineer

Burlingame, CA

$125K - $148K/yr

Meta Reality Labs is seeking a Machine Learning Engineer to drive the productization of gesture recognition models for our AR/VR devices. This role brid.

Meta

Computer Vision Engineer

Redmond, WA

$124K - $147K/yr

The Reality Labs (RL) organization at Meta is helping more people around the world come together and connect through industry-leading Augmented and Virt.

Meta

Computer Vision Engineer

Sunnyvale, CA

$130K - $154K/yr

The Reality Labs (RL) organization at Meta is helping more people around the world come together and connect through industry-leading Augmented and Virt.

Meta

Computer Vision Engineer

Burlingame, CA

$125K - $148K/yr

The Reality Labs (RL) organization at Meta is helping more people around the world come together and connect through industry-leading Augmented and Virt.

Meta

Computer Vision Engineer

Seattle, WA

$126K - $149K/yr

The Reality Labs (RL) organization at Meta is helping more people around the world come together and connect through industry-leading Augmented and Virt.

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Computer Vision Engineer information

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$48.5K

$121.5K

$137.5K

How much do computer vision engineer jobs pay per year?

As of Jul 21, 2026, the average yearly pay for computer vision 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 do computer vision engineers do?

Computer vision engineers develop algorithms and models that enable computers to interpret and analyze visual data such as images and videos. They often work with machine learning frameworks, programming languages like Python or C++, and tools such as OpenCV or TensorFlow to create applications in areas like object detection, facial recognition, and autonomous systems.

What engineers make $300,000 a year?

Senior computer vision engineers, especially those with advanced skills in deep learning, machine learning, and experience with tools like TensorFlow or PyTorch, can earn $300,000 or more annually in high-demand industries such as technology, autonomous vehicles, or AI research. Compensation often depends on experience, location, and company size, with some roles in Silicon Valley or major tech firms reaching this level through base salary, bonuses, and stock options.

What are Computer Vision Engineers?

Computer Vision Engineers are professionals who develop algorithms and systems that enable computers to interpret and process visual information from the world, such as images and videos. They work on tasks like object detection, facial recognition, image segmentation, and more, often using machine learning and deep learning techniques. These engineers apply their expertise in fields like robotics, autonomous vehicles, healthcare, and augmented reality, turning raw visual data into actionable insights.

What is the difference between Computer Vision Engineer vs Machine Learning Engineer?

AspectComputer Vision EngineerMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, Electrical Engineering, or related; knowledge of image processing and computer vision librariesBachelor's or Master's in CS, Data Science, or related; strong programming and statistical skills
Work EnvironmentDevelops algorithms for image/video analysis, object detection, and recognition in tech, automotive, or healthcare industriesBuilds models for various data types, including text, images, and structured data across multiple sectors
Employer & Industry UsageTech companies, autonomous vehicles, robotics, healthcareTech firms, finance, e-commerce, healthcare, and research institutions

While both roles involve machine learning techniques, Computer Vision Engineers specialize in developing algorithms for visual data, whereas Machine Learning Engineers work on broader data modeling across various data types. The roles often overlap but differ mainly in focus and application areas.

What are the key skills and qualifications needed to thrive as a Computer Vision Engineer, and why are they important?

To thrive as a Computer Vision Engineer, you need a strong background in computer science, mathematics, and machine learning, often supported by a relevant degree and experience with image processing algorithms. Familiarity with tools and frameworks such as OpenCV, TensorFlow, PyTorch, and proficiency in programming languages like Python or C++ is essential, along with knowledge of deep learning techniques. Analytical thinking, creativity, and effective communication are standout soft skills for this role. These skills and qualities are crucial for developing innovative vision solutions, interpreting complex data, and collaborating efficiently within interdisciplinary teams.

What engineer makes $500,000 a year?

A senior computer vision engineer at top tech companies or in specialized industries can earn $500,000 or more annually, often including bonuses and stock options. These roles typically require advanced skills in machine learning, deep learning, and experience with tools like TensorFlow or PyTorch, along with a strong educational background and years of experience. Compensation varies based on location, company size, and individual expertise.

What Does a Computer Vision Engineer Do?

Computer vision is a branch of artificial intelligence that attempts to replicate human analytical processes by using algorithms and computer models to understand and identify patterns in images. As a computer vision engineer, you use software to handle the processing and analysis of large data populations, and your efforts support the automation of predictive decision-making efforts. Your responsibilities involve research, programming, data analysis, and user interface design. You may work on a variety of exciting development projects like self-driving cars, mobile devices, innovative features and capabilities in sports and entertainment, and the next generation of social media enhancements.

What are some common challenges faced by Computer Vision Engineers when deploying models to production environments?

Computer Vision Engineers often encounter challenges such as ensuring model accuracy in diverse real-world conditions, optimizing models for efficiency on edge devices, and handling large-scale data processing. Deploying models to production requires balancing performance with resource constraints and addressing issues like latency, scalability, and data privacy. Collaborating closely with software engineers and data scientists is crucial to integrate solutions effectively and continuously monitor and improve model performance in live applications.

Will AI replace computer vision engineers?

AI is transforming the field of computer vision, but computer vision engineers are essential for developing, training, and maintaining AI models and systems. Their expertise in algorithms, programming, and domain knowledge ensures the effective application of AI in real-world scenarios, making complete replacement unlikely in the near term.
More about Computer Vision Engineer jobs
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Computer Vision Engineer jobs near you
Infographic showing various Computer Vision Engineer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $121,515 per year, or $58.4 per hour.
Computer Vision Engineer - UAS

Computer Vision Engineer - UAS

T3i, Inc.

San Antonio, TX

$100K - $118K/yr

Full-time

Re-posted 4 days ago

Job description

Job Summary:
T3i builds mission-critical unmanned systems designed to improve U.S. forces' operational effectiveness and battlefield lethality. Our Blackfoot platform is a tactical FPV drone system engineered for reliability, adaptability, survivability, and rapid deployment in demanding operational environments.
We operate in tight feedback loops between design, build, test, and field use, where every flight directly informs the next iteration of the platform. We are a small, fast-moving team that values ownership, technical depth, execution, and mission focus.
We are seeking a Computer Vision Engineer (CVE) to develop the Blackfoot’s perception and visual autonomy stack. This role is critical to delivering robust onboard vision capabilities - object detection, tracking, visual-inertial navigation, and last-mile terminal guidance - that perform reliably in degraded, GPS-denied, and EW-contested environments.
The CVE will own the design, training, optimization, and deployment of computer vision models running on resource-constrained embedded hardware, working directly with flight software, autonomy, and hardware teams to translate algorithms into deployed capability.
Position Summary:
The CVE will lead the development of real-time perception algorithms for the Blackfoot platform, including detection, classification, tracking, visual odometry, and target lock / terminal guidance. This role emphasizes building models and pipelines that are not only accurate, but small, fast, and resilient under real-world operating conditions - motion blur, low light, adverse weather, occlusion, and adversarial RF/visual environments.
The ideal candidate is equally comfortable writing custom CV algorithms from scratch, training and optimizing neural networks, integrating models onto embedded computers (Jetson, Hailo, Ambarella, or similar), and iterating against real flight data captured by our test pilots. Strong classical computer vision fundamentals - camera calibration, multi-view geometry, feature matching, and bundle adjustment - are as important as modern deep learning.
This role is ideal for someone who thrives in fast-paced R amp;D environments where models are deployed to airframes within days, not quarters, and where flight-test feedback directly drives the next training cycle.
Primary Responsibilities:
  • Design, train, evaluate, and deploy computer vision models for detection, classification, segmentation, tracking, and re-identification of ground and aerial targets
  • Develop and harden visual-inertial odometry (VIO), visual SLAM, and GPS-denied navigation capabilities for tactical FPV operations
  • Build and maintain target lock, terminal guidance, and last-mile autonomy perception pipelines aligned with operational mission requirements
  • Write custom computer vision algorithms from scratch where library implementations don't meet platform constraints (real-time, embedded, adversarial conditions)
  • Own camera and sensor integration: calibration workflows, intrinsic/extrinsic estimation, multi-sensor synchronization, and image pipeline development across RGB, thermal/IR, and stereo modalities
  • Optimize models for real-time inference on embedded edge compute platforms (NVIDIA Jetson, Hailo, Ambarella, Qualcomm, or similar) using TensorRT, ONNX, quantization, pruning, and distillation techniques
  • Write production-quality C++ and Python inference code integrated with onboard flight software and autonomy stacks; apply GPU/CUDA programming for accelerated processing where required
  • Curate, label, and manage flight-collected datasets; build data pipelines for ingestion, augmentation, versioning, and retraining
  • Establish evaluation frameworks and validate perception capabilities across the full test stack: unit tests, simulation, software-in-the-loop, hardware-in-the-loop, and live flight testing
  • Collaborate with autonomy, flight software, and hardware teams to define camera, sensor, and compute requirements; make pragmatic engineering tradeoffs under SWaP constraints
  • Support flight-test campaigns by analyzing onboard video, telemetry, and inference logs to diagnose model failures and prioritize improvements
  • Investigate and integrate emerging techniques in foundation models, multimodal perception, sensor fusion, and on-device learning where they advance platform capability
  • Harden perception against degraded visual conditions (low light, dust, motion blur, occlusion) and against GPS-denied, EW-contested, and visually adversarial environments
  • Document algorithms, models, and pipelines to support team velocity, reproducibility, and customer deliverables
  • Operate effectively in outdoor field environments, including supporting data collection events and live flight testing as required
Required Qualifications:
  • Bachelor's degree in Computer Science, Electrical Engineering, Robotics, Applied Math, or related field
  • 5+ years of hands-on experience developing and deploying computer vision systems (3+ years with an MS, or 2+ years with a PhD)
  • Strong proficiency in modern C++ (C++17 or later) and Python, including writing high-performance code for real-time systems
  • Demonstrated experience writing custom computer vision algorithms - not solely applying existing libraries - optimized for real-time performance
  • Deep experience with PyTorch or TensorFlow, including custom training pipelines, loss design, and large-scale dataset workflows
  • Solid foundation in classical computer vision: camera calibration, multi-view geometry, feature detection/matching, optical flow, bundle adjustment, and pose estimation
  • Solid foundation in modern deep learning architectures for vision (CNNs, transformers, detection/segmentation/tracking heads)
  • Demonstrated experience deploying CV models to embedded or edge compute platforms with hard real-time and SWaP constraints
  • Working knowledge of model optimization techniques: TensorRT, ONNX, quantization (INT8/FP16), pruning, distillation, and compiler-level tuning
  • Experience with OpenCV, Eigen, Ceres, and standard CV/robotics tooling
  • Experience building and maintaining data pipelines for image and video data at scale
  • Ability to validate perception capabilities through simulation, SIL/HIL, and real-world flight test
  • Ability to communicate technical results clearly to engineering, autonomy, and program stakeholders
  • Ability to operate independently, take ownership of full algorithm lifecycle, and iterate rapidly against field feedback
  • Comfortable working in an iterative R amp;D environment with rapidly changing requirements and priorities
  • U.S. Person status required to support ITAR-controlled programs
Preferred Qualifications:
  • Master's or PhD in Computer Vision, Machine Learning, Robotics, or related field
  • Prior experience developing perception or autonomy for UAS, robotics, autonomous vehicles, or defense platforms
  • Experience with on-vehicle perception on dynamic platforms (high angular rates, rapid scene changes, motion blur)
  • Experience with visual-inertial odometry (VIO), visual SLAM, and GPS-denied navigation
  • Experience with single- and multi-object tracking (MOT), re-identification, and tracking through occlusion or sensor handoff
  • Experience developing target lock, terminal guidance, or last-mile autonomy systems
  • Experience with sensor fusion across camera, IMU, GNSS, radar, LiDAR, or thermal modalities
  • Experience with thermal/IR imagery, low-light imaging, event-based vision, or stereo/RGB-D systems
  • Experience with GPU/CUDA programming for accelerated computer vision processing
  • Experience training and deploying foundation models, vision-language models, or self-supervised learning approaches
  • Experience operating in GPS-denied, contested, or EW-affected environments
  • Experience with synthetic data generation, sim-to-real transfer, or domain randomization (Unreal/Unity/Isaac Sim, Gazebo)
  • Familiarity with NVIDIA Jetson Orin, Hailo, Ambarella, Qualcomm RB-series, or similar edge platforms
  • Familiarity with DoD test ranges, COA operations, or military customer environments
  • Active or prior security clearance
  • Experience working in fast-paced defense or dual-use technology environments
  • Publications, open-source contributions, or competition results (KITTI, COCO, nuScenes, etc.) demonstrating CV expertise
Why Join T3i?
  • Direct impact on systems supporting U.S. military capability
  • Small, highly technical team with rapid decision-making and execution
  • Opportunity to shape next-generation tactical FPV platforms from prototype through operational deployment
  • High level of ownership and autonomy
  • Exposure to advanced autonomy, RF, payload, and tactical UAS development efforts
Type of Employment: Part-Time (20–30 hours/week initially, with potential to transition to full-time)

Travel: ~25% travel to test ranges, customer demonstrations, and field exercises
Compensation: Part-time: $72 - $96 per hour (Full-time equivalent $150,000 - $200,000) based on experience and qualifications
Clearance Requirements: Desire and ability to obtain a Secret clearance
Required Background Check: HireRight background check amp; drug screening
T3i Drug Free Workplace Statement:
As a Federal Government Contractor, T3i is required to strictly adhere to federally mandated drug-free workplace standards. To ensure compliance with this requirement, T3i conducts pre-employment drug screening for all new hire personnel (full time, part time, and independent contractor) and annual random drug screening for all current T3i personnel. Personnel who cannot pass drug screening are not eligible for employment with T3i.
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About T3i

Sourced by ZipRecruiter

Industry

Guided missile and space vehicle manufacturing

Company size

51 - 200 Employees

Headquarters location

San Diego, CA, US

Year founded

2014

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