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Computer Vision Engineer Jobs in Dallas, TX (NOW HIRING)

Job Summary We are seeking a highly skilled AI Engineer to design, develop, and deploy scalable AI ... Experience with computer vision solutions using OpenCV. Key Responsibilities * Design, develop, and ...

Senior AI Engineer

Dallas, TX · On-site

$103K - $142K/yr

Experience with natural language processing (NLP) or computer vision applications. * Knowledge of MLOps principles and tools. * Familiarity with version control systems (e.g., Git) and Agile ...

Background in NLP, computer vision, or other advanced AI techniques. * Relevant certifications (Coursera, edX, AWS, Azure, Google Cloud). Required qualifications: * Strong programming skills in ...

Senior AI Engineer

Dallas, TX · On-site

$103K - $142K/yr

Experience with natural language processing (NLP) or computer vision applications. * Knowledge of MLOps principles and tools. * Familiarity with version control systems (e.g., Git) and Agile ...

Angular Developer

Irving, TX · On-site

$52.50 - $64.25/hr

Angular Developer Must Have Technical/Functional Skills: 8+ Years of experience with Angular ... and computer vision, tailored to specific needs Evaluate and compare different AI model ...

New

Angular Developer

Irving, TX · On-site

$50.75 - $62.25/hr

Tata Consultancy Services is seeking an Angular Developer to design and implement advanced AI ... computer vision, tailored to specific needs • Evaluate and compare different AI model ...

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Computer Vision Engineer information

See Dallas, TX salary details

$48.2K

$120.7K

$136.6K

How much do computer vision engineer jobs pay per year?

As of Jul 12, 2026, the average yearly pay for computer vision engineer in Dallas, TX is $120,719.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,800.00 and $130,600.00 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 Dallas, TX? The most popular types of Computer Vision Engineer jobs in Dallas, TX are:
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What cities near Dallas, TX are hiring for Computer Vision Engineer jobs? Cities near Dallas, TX with the most Computer Vision Engineer job openings:

Director of Applied AI & ML Engineering

Paradigm

Irving, TX • Remote

Full-time

Re-posted 28 days ago


Job description

Paradigm is a software company transforming the way that the residential construction & building product industries operate across the globe. We are looking for a Director, Applied AI & ML Engineering to be part of revolutionizing these industries.

The Director, Applied AI & ML Engineering will lead the strategy, architecture, and deployment of intelligent systems that transform how homes are designed, estimated, and built. This role will drive the integration of AI and machine learning across the residential construction lifecycle—from digital plan understanding and takeoffs to automated estimating, material optimization, and design personalization.

The ideal leader blends technical depth with strategic clarity—able to guide teams across computer vision, large language models, and agentic automation while ensuring reliable, scalable delivery within the construction domain.

What You Will Do:

  • Define and lead the Applied AI & ML strategy for residential construction, identifying and prioritizing use cases that enhance speed, accuracy, and efficiency.

  • Build and maintain a roadmap of agentic AI systems that automate key construction workflows—such as plan interpretation, quantity takeoffs, cost estimation, and material specification optimization, while enabling seamless integration with suppliers, ERP platforms, and technology providers.

  • Partner with Product, Engineering, and Operations leaders to embed AI capabilities into core platforms and customer-facing applications.

  • Lead the design of AI-powered and multi-agent systems that connect workflows across design, estimating, procurement, and field execution.

  • Architect retrieval-augmented generation (RAG) and computer vision pipelines that interpret plan sets, generate takeoffs, and surface contextual insights.

  • Combine LLMs, CV, and rule-based logic to deliver explainable and auditable systems tailored to construction professionals.

  • Ensure architectural scalability, performance, and observability in all deployed systems.

  • Oversee the end-to-end ML lifecycle—from experimentation and model development to deployment, monitoring, and iteration.

  • Implement best practices in MLOps, data management, and continuous delivery pipelines.

  • Deliver measurable improvements in model quality, reasoning accuracy, and cost efficiency through advanced evaluation methods, such as Evals, zero- and few-shot benchmarking, Chain-of-Thought, and LLM-as-a-judge techniques to guide continuous model refinement.

  • Build, mentor, and lead a cross-functional team of applied AI and ML engineers, partnering closely with product, design, and software engineering teams to deliver production-grade AI-powered systems.

  • Foster a culture of collaboration, experimentation, and responsible AI development.

  • Manage vendor relationships and technology partnerships across cloud and AI platforms.

  • Collaborate with design, estimating, and operations teams to identify automation opportunities and ensure successful adoption.

  • Translate complex AI concepts into clear direction for business and product stakeholders.

  • Represent the organization’s AI vision in external partnerships, technical forums, and industry collaborations.

What You Need to Succeed:

  • 12+ years of experience in applied AI, ML, and/or Software engineering, with at least 5 years in a leadership role.

  • Bachelor’s or advanced degree in Computer Science, Machine Learning, or a related field preferred.

  • Proven success designing and deploying AI-driven systems in production environments.

  • Expertise in LLMs, computer vision, multimodal models, and retrieval-augmented generation (RAG) architectures.

  • Strong foundation in modern software engineering—including APIs, microservices, CI/CD, and containerization.

  • Hands-on familiarity with ML platforms such as MLflow, Kubeflow, or SageMaker for model training and deployment.

  • Demonstrated ability to collaborate across engineering, product, and operations in a complex technical environment.

  • Excellent written and verbal communication skills for both technical and executive audiences.

  • Experience in residential construction technology, including estimating, takeoffs, or design automation is preferred.

  • Background in BIM/CAD integration, digital twin platforms, or 3D modeling workflows is preferred.

  • Familiarity with agent orchestration frameworks (Temporal, n8n, LangGraph) and enterprise API integration is preferred.

  • Understanding of AI governance, auditability, and human-in-the-loop validation frameworks is preferred.

  • Experience with Azure, AWS, or GCP cloud platforms for scalable AI deployment is preferred.

Ready to Join? Apply now! MyParadigm.com/careers/
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