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Computer Vision Engineer Jobs in Buffalo, NY (NOW HIRING)

acv

Embedded Systems Engineer IV, R&D

Buffalo, NY · On-site

As an Engineer IV, Embedded Systems within the R&D team, you will serve as a technical anchor for ... and computer vision pipelines. * System Stability & Lifecycle: Design robust fault-detection ...

ACV

Embedded Systems Engineer IV, R&D

Buffalo, NY · On-site

$139K - $174K/yr

As an Engineer IV, Embedded Systems within the R&D team, you will serve as a technical anchor for ... and computer vision pipelines. * System Stability & Lifecycle: Design robust fault-detection ...

Stark Tech

Design Engineer I

Buffalo, NY · On-site

$63K - $84K/yr

Advanced computer skills and proficiency in MS Office Suite required. * Must be able to deal with a ... Guided by our mission, vision, and values, we focus on hiring candidates who are aligned with our ...

Stark Tech

Design Engineer I

Buffalo, NY · On-site

$63K - $105K/yr

Advanced computer skills and proficiency in MS Office Suite required. * Must be able to deal with a ... and vision coverage, generous employer HSA contributions, paid time off, a 401(k) with employer ...

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Showing results 21-40

All JobsComputer Vision Engineer JobsComputer Vision Engineer Jobs in Buffalo, NY

Computer Vision Engineer information

See Buffalo, NY salary details

$47K

$117.7K

$133.2K

How much do computer vision engineer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for computer vision engineer in Buffalo, NY is $117,708.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,000.00 and $127,400.00 per year, depending on experience, location, and employer.

What is a computer vision engineer?

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 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.
More about Computer Vision Engineer jobs

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For Computer Vision Engineer jobs in Buffalo, NY, the most frequently searched job titles are:

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The top searched job categories for Computer Vision Engineer jobs in Buffalo, NY are:

What cities near Buffalo, NY are hiring for Computer Vision Engineer jobs?

Cities near Buffalo, NY with the most Computer Vision Engineer job openings:

Computer Vision Engineer jobs near you
Infographic showing various Computer Vision Engineer job openings in Buffalo, NY as of August 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 88% In-person, 6% Hybrid, and 6% Remote job distribution, with an average salary of $117,708 per year, or $56.6 per hour.

Embedded Systems Engineer IV, R&D

acv

Buffalo, NY • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Who we are looking for:

As an Engineer IV, Embedded Systems within the R&D team, you will serve as a technical anchor for our next-generation hardware platforms. You will design, develop, and optimize high-performance software running on a variety of embedded systems—ranging from single-board computers and edge AI compute modules to custom ARM architecture.

This role requires a unique blend of scrappy, proof-of-concept rapid prototyping and disciplined, production-grade software engineering. You will own the software lifecycle for new devices, ensuring seamless integration between low-level hardware, sensors, edge computing frameworks, and our enterprise cloud infrastructure.

What you will do:

  • End-to-End Development: Architect, implement, and maintain embedded software from initial conceptual prototypes to ruggedized, scalable, enterprise-level production code.
  • Platform Ownership: Develop and optimize firmware and middleware on platforms including Raspberry Pi, NVIDIA Jetson, and ARM-based System-on-Modules (SOMs).
  • Sensor & Peripheral Integration: Write and debug low-level drivers and interfaces for a diverse ecosystem of peripherals, cameras, and environmental sensors via protocols such as I2C, SPI, UART, USB, and PCIe.
  • Edge Intelligence & Compute: Optimize software on compute-constrained edge devices, including leveraging hardware acceleration (e.g., CUDA, TensorRT on Jetson platforms) for real-time data processing and computer vision pipelines.
  • System Stability & Lifecycle: Design robust fault-detection, automated recovery mechanisms, and secure over-the-air (OTA) firmware update systems to ensure maximum field stability.
  • Cross-Functional Collaboration: Partner closely with hardware/electrical engineers, mechanical designers, and cloud backend teams to define system architectures and interfaces.
  • Mentorship & Standards: Drive code quality through rigorous code reviews, automated testing, and comprehensive documentation. Mentor junior and mid-level engineers on the team.
  • Perform additional duties as assigned.

What you will need:

  • Ability to read, write, speak and understand English.
  • BS degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field (or equivalent practical experience).
  • 6+ years’ Professional experience in embedded software development, with a proven track record of shipping commercial or industrial hardware products
  • Expert-level proficiency in C and C++; strong scripting skills in Python or Bash for testing and automation.
  • OS Expertise: Deep experience developing within Embedded Linux environments (including kernel configuration, device tree modification, and custom driver development).
  • Hands-on experience building applications on Raspberry Pi (Linux/Debian) and NVIDIA Jetson (JetPack ecosystem).
  • Solid understanding of hardware communication protocols: SPI, I2C, UART, CAN bus, USB.
  • Experience interfacing with high-resolution image sensors, cameras, or specialized sensors.
  • Proficiency with modern software engineering tools: Git, CMake, Docker, and CI/CD pipelines tailored for embedded targets.
  • Familiarity with networking stacks and IoT communication protocols (TCP/IP, UDP, MQTT, gRPC).
  • Comfortable utilizing lab equipment like oscilloscopes, logic analyzers, and multimeters to debug hardware/software boundary issues.
  • Expert in version control systems including trunk-based development, multiple release planning, cherry picking, and rebase.
  • Nice to Have Technical Competencies
    • Experience with custom Linux distribution builders like Yocto Project or Buildroot.
    • Familiarity with real-time operating systems (RTOS) or bare-metal ARM development.
    • Experience deploying or optimizing machine learning models at the edge.

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