Job description

Role purpose Develop synthetic-data pipelines and AI experiments for perception and physical-AI use cases using simulated industrial environments and sensor outputs. Key responsibilities • Generate labeled image, video, point-cloud, depth, segmentation, pose, and scene data from simulation. • Design domain randomization, scenario coverage, class balancing, and dataset versioning. • Train and evaluate perception models using synthetic, real, and blended datasets. • Measure domain gap and improve transfer through simulation, augmentation, adaptation, and targeted real data. • Automate experiments, metadata capture, quality checks, and reproducible releases. Required experience and skills • Computer vision or ML engineering plus synthetic-data experience. • Python and deep-learning frameworks. • Understanding of labels, ground truth, dataset bias, evaluation, and experiment reproducibility. Preferred experience Omniverse Replicator, Isaac Sim, diffusion models, YOLO/RF-DETR, segmentation, point clouds, domain adaptation, or MLOps. Salary Range: $90,000 - $150,000 per year TCS Employee Benefits Summary: Discretionary Annual Incentive. Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans. Family Support: Maternal & Parental Leaves. Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement. Time Off: Vacation, Time Off, Sick Leave & Holidays. Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Requirements

Must-haves

Role purpose
Develop synthetic-data pipelines and AI experiments for perception and physical-AI use cases using
simulated industrial environments and sensor outputs.
Generate labeled image, video, point-cloud, depth, segmentation, pose, and scene data from
Design domain randomization, scenario coverage, class balancing, and dataset versioning.
Train and evaluate perception models using synthetic, real, and blended datasets.
Measure domain gap and improve transfer through simulation, augmentation, adaptation, and
targeted real data.
Automate experiments, metadata capture, quality checks, and reproducible releases.
Required experience and skills
Computer vision or ML engineering plus synthetic-data experience.
Python and deep-learning frameworks.
Understanding of labels, ground truth, dataset bias, evaluation, and experiment reproducibility.
Discretionary Annual Incentive.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Time Off: Vacation, Time Off, Sick Leave & Holidays.

Nice-to-haves

Omniverse Replicator, Isaac Sim, diffusion models, YOLO/RF-DETR, segmentation, point clouds,
domain adaptation, or MLOps.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlpython

Platform: careers-page
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Parental Leave