Tata Consultancy Services
Computer Vision Engineer
Pay Range:
$90,000 - $140,000 per annum
Job Type:
Full Time
Responsibilities
Develop classical image processing techniques for NDT (filtering, edge detection, thresholding) used with machine learning models.
Process point clouds and perform 3D geometry analysis for flaw detection.
Design, train, and optimize deep learning models (3D CNNs, Vision Transformers, U-Nets) for flaw detection, segmentation, and classification in volumetric CT data and 2D X-ray images.
Develop rigorous validation frameworks to measure model performance against expert NDT technician analysis, ensuring precision and recall meet industry standards.
Build robust data pipelines for ingesting, preprocessing, and augmenting large-scale volumetric CT data, addressing noise reduction, normalization, and material attenuation artifacts.
Integrate models into real-time production line inspection systems, optimizing for high-speed inference and edge deployment.
Collaborate with NDT Level II/III technicians to understand defectology and define accurate labeling protocols.
Work with mechanical and materials engineers to incorporate domain knowledge (material properties, expected stress points) into model design.
Monitor model performance in production, implementing active learning and data drift detection strategies to continuously improve system accuracy.
Qualifications & Experience
Experience with point cloud processing and 3D geometry analysis.
Knowledge of industry standards and regulations (NADCAP, AS9100, ISO 9001) related to quality control and NDT processes.
Familiarity with robotics, PLCs, and industrial automation systems (Siemens, Fanuc).
Strong background in deep learning model development for 3D volumetric data.
Proven ability to develop data pipelines for large-scale scientific data.
Excellent collaboration skills with cross-functional teams.
Continuous improvement mindset with active learning experience.
Benefits Summary
Discretionary annual incentive.
Comprehensive medical coverage (medical, dental, vision, disability, pet insurance).
Family support (maternal & parental leaves).
Auto & home insurance, identity theft protection.
Commuter benefits, certification & training reimbursement.
Paid time off (vacation, sick leave, holidays).
401(k) plan, performance bonus, college fund, student loan refinancing.
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$90,000 - $140,000 per annum
Job Type:
Full Time
Responsibilities
Develop classical image processing techniques for NDT (filtering, edge detection, thresholding) used with machine learning models.
Process point clouds and perform 3D geometry analysis for flaw detection.
Design, train, and optimize deep learning models (3D CNNs, Vision Transformers, U-Nets) for flaw detection, segmentation, and classification in volumetric CT data and 2D X-ray images.
Develop rigorous validation frameworks to measure model performance against expert NDT technician analysis, ensuring precision and recall meet industry standards.
Build robust data pipelines for ingesting, preprocessing, and augmenting large-scale volumetric CT data, addressing noise reduction, normalization, and material attenuation artifacts.
Integrate models into real-time production line inspection systems, optimizing for high-speed inference and edge deployment.
Collaborate with NDT Level II/III technicians to understand defectology and define accurate labeling protocols.
Work with mechanical and materials engineers to incorporate domain knowledge (material properties, expected stress points) into model design.
Monitor model performance in production, implementing active learning and data drift detection strategies to continuously improve system accuracy.
Qualifications & Experience
Experience with point cloud processing and 3D geometry analysis.
Knowledge of industry standards and regulations (NADCAP, AS9100, ISO 9001) related to quality control and NDT processes.
Familiarity with robotics, PLCs, and industrial automation systems (Siemens, Fanuc).
Strong background in deep learning model development for 3D volumetric data.
Proven ability to develop data pipelines for large-scale scientific data.
Excellent collaboration skills with cross-functional teams.
Continuous improvement mindset with active learning experience.
Benefits Summary
Discretionary annual incentive.
Comprehensive medical coverage (medical, dental, vision, disability, pet insurance).
Family support (maternal & parental leaves).
Auto & home insurance, identity theft protection.
Commuter benefits, certification & training reimbursement.
Paid time off (vacation, sick leave, holidays).
401(k) plan, performance bonus, college fund, student loan refinancing.
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