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Computer Vision Engineer Jobs in Boston, MA (NOW HIRING)

AI/ML Engineer

Boston, MA · On-site

$30 - $35/hr

Develop AI-powered applications using NLP, Computer Vision, Generative AI, and predictive analytics ... Collaborate with data engineers, software developers, and business stakeholders to understand ...

AI/ML Engineer

Boston, MA · On-site

$35 - $45/hr

Develop AI-powered applications using NLP, Computer Vision, Generative AI, and predictive analytics ... Collaborate with data engineers, software developers, and business stakeholders to understand ...

Job Summary (AI Engineer): - Work as an AI Engineer for an information management company. - Hybrid ... or computer vision (OpenCV). - Flexible on background/drug screening requirements. - LinkedIn ...

Senior Machine Learning Engineer

Boston, MA · On-site

$170K - $205K/yr

About the position: We're looking for a Senior Machine Learning Engineer with deep expertise in ... and computer vision teams. This is an opportunity to design, build, and scale machine learning ...

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Computer Vision Engineer information

See Boston, MA salary details

$52.7K

$132K

$149.4K

How much do computer vision engineer jobs pay per year?

As of Jul 4, 2026, the average yearly pay for computer vision engineer in Boston, MA is $132,007.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,100.00 and $142,900.00 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.
What are the most commonly searched types of Computer Vision Engineer jobs in Boston, MA? The most popular types of Computer Vision Engineer jobs in Boston, MA are:
What are popular job titles related to Computer Vision Engineer jobs in Boston, MA? For Computer Vision Engineer jobs in Boston, MA, the most frequently searched job titles are:
What cities near Boston, MA are hiring for Computer Vision Engineer jobs? Cities near Boston, MA with the most Computer Vision Engineer job openings:
Infographic showing various Computer Vision Engineer job openings in Boston, MA as of June 2026, with employment types broken down into 40% Full Time, 50% Part Time, and 10% Contract. Highlights an 95% Physical, 2% Hybrid, and 3% Remote job distribution, with an average salary of $132,007 per year, or $63.5 per hour.
Software Engineer, AI Systems

Software Engineer, AI Systems

Aptima Inc. (All Jobs)

Woburn, MA • On-site

Full-time

Posted 7 days ago


Job description

Description:

Who We Are

Aptima is a technological leader in the national security industry. Our mission is to drive the future of national security by engineering scalable solutions that fuse technological innovation with human potential to transform how individuals and teams train, develop, and perform in mission-critical environments.


Our culture is rooted in our core values, which have evolved over time and our employees have embraced: Integrity, Ingenuity, Excellence, Respect, Engagement, Teamwork. At our core, Aptima researches, develops, and innovates within an area that engineering firms largely ignore, the human component. To impact the world in meaningful ways, you must bring those innovations to light, and that is precisely what we do.


How You’ll Make an Impact


Operating in the Dayton area and collaborating closely with Department of War (DoW) research customers, you will design, develop, deploy, and sustain advanced AI-enabled software systems that solve complex, mission-critical problems. You will work across the full lifecycle—from prototyping and fine-tuning AI models to engineering scalable applications and deploying production-ready solutions into operational environments. Whether building large language model applications, computer vision pipelines, multimodal AI systems, or agentic workflows, your work will directly support military readiness and innovation.


In this role, you will bridge AI research and software engineering by transforming cutting-edge algorithms into robust, maintainable, and deployable systems. You will work hands-on with real-world datasets, build backend services and APIs, integrate AI models into software architectures, and collaborate closely with researchers, data scientists, and software engineers to deliver high-quality operational capabilities. By combining strong AI expertise with software engineering best practices, you will help advance the next generation of intelligent systems for defense applications.


Key Responsibilities

  • Design, develop, deploy, and maintain AI-enabled software systems that leverage multimodal data sources to classify, assess, and model human performance and operational behaviors.
  • Build and integrate AI capabilities—including LLMs, agentic systems, computer vision models, and multimodal analytics—into scalable software applications and services.
  • Design and implement backend services, APIs, workflows, and software infrastructure that support production AI applications.
  • Collaborate within agile, cross-functional teams to transition research algorithms into operational software systems.
  • Develop, test, containerize, deploy, and maintain production-ready applications using modern software engineering and DevSecOps practices.
  • Contribute to software architecture, system integration, testing, CI/CD pipelines, and cloud or edge deployment strategies.
  • Successfully design and implement scientific and technical components of projects and proposals.
  • Lead execution of technical tasks, ensuring work is delivered with high quality and on schedule.
  • Contribute to technical reports, publications, presentations, proposals, and customer deliverables.
  • Support customer engagements through software demonstrations, integration activities, technical discussions, and capability briefings.
  • Continue professional development through conferences, technical literature, and emerging technologies in AI and software engineering.
  • Present work through professional publications, technical forums, and conferences.
Requirements:
  • 3-5 years of relevant experience and ability to obtain and maintain a US Government Security Clearance.
  • Willingness to travel when necessary
  • Demonstrated technical ability and initiative to lead and execute work independently.
  • Understanding across multiple technical domains, with expertise spanning AI/ML and software engineering.
  • Ability to apply engineering principles and software development practices to produce high-quality, customer-focused technical solutions.
  • Strong software engineering experience, including:
  1. Object-oriented programming (Python preferred; Java, C#, or similar languages a plus).
  2. Software architecture and modular design principles.
  3. API and backend service development.
  4. Version control and collaborative development workflows.
  5. Testing, debugging, and production software practices.
  6. Containerization and deployment technologies (Docker, Kubernetes, CI/CD pipelines).
  • Experience building AI/ML systems using frameworks such as:
  1. PyTorch, TensorFlow, Hugging Face, LangChain, or similar tools.
  2. LLMs, NLP, agentic AI workflows, computer vision, or multimodal systems.
  3. Data processing pipelines and model development from large datasets.
  • Experience deploying AI models into operational environments, cloud platforms, or edge systems preferred.
  • Familiarity with MOSA, MBSE, and Government Reference Architectures, including modular design, defined interfaces, and standards-based integration is preferred
  • Familiarity with MLOps, cloud technologies (AWS, Azure, Kubernetes), and scalable deployment architectures is a plus.
  • Experience translating research prototypes into maintainable, production-quality systems strongly preferred.


All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or any other status protected by applicable national, federal, state or local law.