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Embedded Computer Vision Jobs (NOW HIRING)

Computer Vision Engineer

San Diego, CA · On-site

$125K - $130K/yr

... embedded and desktop systems * Optimize performance using multithreading, SIMD, and GPU ... or related field * 3+ years of computer vision experience in real-time, product-focused ...

Computer Vision Engineer

San Diego, CA · On-site

$150 - $200/hr

Experience with real ‑ time computer vision systems or embedded AI deployment.Experience using performance profiling tools and hardware simulators.Level of ResponsibilityWorks independently with ...

Computer Vision Engineer

San Diego, CA · On-site

$118K - $139K/yr

Experience with real-time computer vision systems or embedded AI deployment. * Experience using performance profiling tools and hardware simulators. Level of Responsibility * Works independently with ...

Computer Vision Engineer

San Diego, CA · On-site

$150 - $200/hr

Experience with real‑time computer vision systems or embedded AI deployment. * Experience using ... performance profiling tools and hardware simulators. Level of Responsibility * Works independently ...

Computer Vision Engineer

San Jose, CA · On-site

$140K - $260K/yr

Design and implement deep-learning and classical computer vision algorithms for real-time, embedded deployment * Perform sensor calibration and multi-sensor fusion across camera, lidar, and radar

Computer Vision Engineer

Santa Clara, CA · On-site

$131K - $155K/yr

... Computer Vision. We are looking for excellent problem solvers to: * Contribute to multi-sensor data ... Experience with deploying custom software to embedded CPUs, GPUs, or FPGAs * Previous work with ...

Computer Vision/ML Engineer

Brooklyn, NY · On-site

$121K - $142K/yr

Responsibilities : • Design, fine-tune, and deploy computer vision models (YOLO, InsightFace ... for embedded deployment using quantization, pruning, TensorRT, and NVIDIA Triton • Build and ...

Computer Vision Engineer

Santa Clara, CA · On-site

$131K - $155K/yr

... Computer Vision. We are looking for excellent problem solvers to: * Contribute to multi-sensor data ... Experience with deploying custom software to embedded CPUs, GPUs, or FPGAs * Previous work with ...

Computer Vision/ML Engineer

New York, NY · On-site

$122K - $143K/yr

What you will do: * Design, fine-tune, and deploy computer vision models (YOLO, InsightFace ... Optimize models for embedded deployment using quantization, pruning, TensorRT, and NVIDIA Triton

Computer Vision/ML Engineer

Brooklyn, NY · On-site

$117K - $138K/yr

What you will do: * Design, fine-tune, and deploy computer vision models (YOLO, InsightFace ... Optimize models for embedded deployment using quantization, pruning, TensorRT, and NVIDIA Triton

Computer Vision Engineer - UAS

San Antonio, TX · On-site

$100K - $118K/yr

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 / IoT product experience, particularly with computer vision and cameras for embedded systems The estimated base salary range for this position is $220-250K, which does not include the value ...

Computer Vision/ML Engineer

Brooklyn, NY · On-site

$117K - $138K/yr

What you will do: * Design, fine-tune, and deploy computer vision models (YOLO, InsightFace ... Optimize models for embedded deployment using quantization, pruning, TensorRT, and NVIDIA Triton

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Embedded Computer Vision information

See salary details

$70K

$153.4K

$174K

How much do embedded computer vision jobs pay per year?

As of Sep 9, 2026, the average yearly pay for embedded computer vision in the United States is $153,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What is embedded computer vision?

Embedded computer vision refers to the integration of computer vision algorithms and techniques directly into hardware devices, such as cameras, smartphones, autonomous vehicles, or industrial machinery. Unlike traditional computer vision systems that require powerful external computers, embedded computer vision systems process visual data locally on devices with limited resources. This allows for real-time image and video analysis, lower latency, improved privacy, and reduced energy consumption, making them ideal for applications like robotics, surveillance, and IoT devices.

What are the key skills and qualifications needed to thrive as an embedded computer vision engineer?

To thrive as an Embedded Computer Vision Engineer, you generally need strong programming skills in C/C++, a deep understanding of computer vision algorithms, and experience with embedded systems, often supported by a degree in computer engineering or a related field. Familiarity with tools and frameworks like OpenCV, TensorFlow Lite, and hardware platforms such as ARM Cortex or NVIDIA Jetson, as well as relevant certifications, is highly valuable. Critical soft skills include problem-solving, attention to detail, and effective communication for collaborating with multidisciplinary teams. These competencies ensure robust, efficient deployment of vision solutions on resource-constrained devices, driving innovation and product performance.

What are some typical challenges faced by professionals in embedded computer vision roles, and how can they be addressed?

Professionals in embedded computer vision often encounter challenges such as limited processing power, memory constraints, and real-time performance requirements on edge devices. To address these, it's essential to optimize algorithms for efficiency, leverage hardware accelerators (like GPUs or dedicated vision processors), and carefully manage memory usage. Collaboration with hardware engineers and software developers is common to ensure that solutions are both performant and scalable. Staying updated with the latest advances in model compression and efficient neural network architectures is also critical for success in this role.

What other helpful pages are available for Embedded Computer Vision?

Other pages related to Embedded Computer Vision:

Infographic showing various Embedded Computer Vision job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 77% Full Time, 16% Part Time, and 6% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.

Computer Vision Engineer

San Diego, CA • On-site

$100 - $125/hr

Other

Posted 7 days ago


Job description

Join a fast-moving team building real-time vision systems that power advanced tracking and simulation technology. In this role, you will design and implement computer vision solutions that track objects and motion using high-speed, multi-camera data in a hardware-integrated environment.

What You’ll Do

Develop real-time algorithms for object detection, tracking, pose estimation, and motion analysis

Process high-frame-rate, multi-camera data to generate accurate 3D trajectories and impact insights

Collaborate with hardware, firmware, and simulation teams to integrate vision pipelines into embedded and desktop systems

Optimize performance using multithreading, SIMD, and GPU acceleration

Apply camera calibration, stereo vision, and sensor fusion for precise spatial modeling

Prototype new concepts, evaluate sensors, and support field testing

Write clean, testable code with unit and integration testing

Document algorithms, workflows, and data pipelines

Support ML workflows including dataset versioning, experiment tracking, and deployment (Azure ML)

Required Qualifications

Bachelor’s or Master’s in Computer Science, Computer Engineering, Electrical Engineering, or related field

3+ years of computer vision experience in real-time, product-focused environments

Strong Python skills with OpenCV or similar libraries

Solid understanding of camera geometry, calibration, and lens distortion correction

Experience with multi-camera systems, stereo vision, or 3D reconstruction

Knowledge of tracking techniques (optical flow, Kalman filters, background subtraction, deep learning)

Experience with real-time optimization, parallel processing, or embedded CV deployment

Preferred Qualifications

C++, PyTorch, or TensorFlow experience

GPU programming (CUDA/OpenGL)

Embedded systems or real-time video pipelines

MATLAB or ROS exposure

Docker and containerized ML workflows

Azure ML DevOps pipelines for automated training and deployment

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