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Machine Vision & AI Engineer Manufacturing (Dallas)
Machine Vision & AI Engineer Manufacturing (Dallas)Yoh, A Day & Zimmermann Company • Dallas, TX, US
Machine Vision & AI Engineer Manufacturing (Dallas)

Machine Vision & AI Engineer Manufacturing (Dallas)

Yoh, A Day & Zimmermann Company • Dallas, TX, US
Hace 17 horas
Tipo de contrato
  • A tiempo parcial
  • Indefinido
Descripción del trabajo

Machine Vision & AI Engineer Manufacturing

Direct Hire

Hy brid (Joplin, MO; Dallas, TX; Phillipsburg, KS; Tuscaloosa, AL; or Frederick, MD)

Position Summary This role is responsible for developing, implementing, and sustaining both traditional and AI-driven machine vision systems used to ensure the quality of building material products. The position supports production environments across multiple manufacturing sites and requires hands-on involvement with data pipelines, model development, hardware configuration, and cross-functional collaboration.

Essential Functions

  • Develop computer vision algorithms and AI / ML models to support automated inspection and defect detection in manufacturing environments.
  • Build and curate image datasets, including identifying data sources, capturing diverse samples, and ensuring accurate image labeling.
  • Clean, preprocess, and prepare image data for training using techniques such as normalization, noise reduction, and data augmentation.
  • Develop and maintain preprocessing and data pipelines to support stable and high-performing vision models.
  • Apply data and sensor fusion techniques to incorporate additional sensor inputs when appropriate.
  • Continuously improve existing models by retraining, tuning, and evaluating performance against new data and real-world feedback.
  • Design and conduct validation tests to ensure models perform reliably under varying manufacturing conditions.
  • Document best practices related to machine vision, model development, and system deployment.
  • Demonstrate familiarity with machine vision hardware, including cameras, lighting, optics, and environmental factors.
  • Stay current on computer vision advancements and evaluate new methods or technologies that may improve system performance.
  • Collaborate closely with engineering, production, and quality teams to improve productivity, efficiency, and accuracy across manufacturing lines.

Preferred Qualifications

  • Bachelors degree in Computer Science, Computer Vision, Machine Learning, Engineering, or related field with at least 3 years of relevant industrial experience
  • OR

    High school diploma / GED with 8+ years of machine vision or engineering experience in a manufacturing setting.

  • Strong programming skills (Python, C, C++, or similar).
  • Experience with machine learning frameworks and modern computer vision models.
  • Experience working with large image datasets and image preprocessing pipelines.
  • Familiarity with data augmentation techniques and various image formats.
  • Experience integrating AI / ML models into production systems or industrial workflows.
  • Experience with containerization tools (e.g., Docker).
  • Background deploying vision-based defect detection in manufacturing environments.
  • Experience with SQL and CUDA.
  • Familiarity with commercial vision software packages.
  • Experience with statistical testing or measurement system analysis.
  • Experience deploying models on edge computing devices for low-latency inference.
  • Knowledge of nondestructive testing techniques.
  • Experience managing technical projects (Agile preferred).
  • Experience creating standardized documentation and training materials.
  • Estimated Min Rate : $105000.00

    Estimated Max Rate : $150000.00

    Whats In It for You?

    We welcome you to be a part of the largest and legendary global staffing companies to meet your career aspirations. Yohs network of client companies has been employing professionals like you for over 65 years in the U.S., UK and Canada. Join Yohs extensive talent community that will provide you with access to Yohs vast network of opportunities and gain access to this exclusive opportunity available to you. Benefit eligibility is in accordance with applicable laws and client requirements. Benefits include :

  • Medical, Prescription, Dental & Vision Benefits (for employees working 20+ hours per week)
  • Health Savings Account (HSA) (for employees working 20+ hours per week)
  • Life & Disability Insurance (for employees working 20+ hours per week)
  • MetLife Voluntary Benefits
  • Employee Assistance Program (EAP)
  • 401K Retirement Savings Plan
  • Direct Deposit & weekly epayroll
  • Referral Bonus Programs
  • Certification and training opportunities
  • Note : Any pay ranges displayed are estimations. Actual pay is determined by an applicant's experience, technical expertise, and other qualifications as listed in the job description. All qualified applicants are welcome to apply.

    Yoh, a Day & Zimmermann company, is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

    Visit https : / / www.yoh.com / applicants-with-disabilities to contact us if you are an individual with a disability and require accommodation in the application process.

    For California applicants, qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. All of the material job duties described in this posting are job duties for which a criminal history may have a direct, adverse, and negative relationship potentially resulting in the withdrawal of a conditional offer of employment.

    By applying and submitting your resume, you authorize Yoh to review and reformat your resume to meet Yohs hiring clients preferences. To learn more about Yohs privacy practices, please see our Candidate Privacy Notice : https : / / www.yoh.com / privacy-notice

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