HCLTech (HCL Technologies) is accepting applications for the position of Campus-Trainee / Computer Vision Engineer II – Vision Model Development & Automation at its Chennai, Tamil Nadu campus.
Designed for Tier-1 fresh graduates and early-career engineers (0 to 1 year of experience), this technical role focuses on building production-ready computer vision pipelines, MLOps automation, and edge/cloud AI integrations across surveillance, smart spaces, and industrial automation domains.
Below is the complete role specification, technical skill set, key responsibilities, and application details.
1. Job Summary Table
Parameter
Specification
Hiring Organization
HCLTech (HCL Technologies Limited)
Role Title
Campus-Trainee / Computer Vision Engineer II
Specialization
Vision Model Development & Automation
Work Location
Chennai, Tamil Nadu, India
Target Audience
Tier-1 Fresh Graduates (0–1 Year Experience)
Employment Type
Full-Time / Permanent
Domain Focus
Computer Vision, MLOps, Deep Learning, Edge & Cloud AI
2. Key Responsibilities & Core Tasks
Selected candidates will take charge of end-to-end vision pipeline engineering and optimization:
End-to-End Vision Pipeline Engineering: Design, build, and optimize complete pipelines covering video ingestion, pre-processing, deep learning inference, post-processing, and metadata generation.
Model Fine-Tuning & Algorithmic Design: Implement state-of-the-art models for object detection, multi-object tracking, re-identification, semantic segmentation, anomaly detection, and Optical Character Recognition (OCR).
High-Performance Acceleration: Collaborate with platform teams to optimize models for low latency and high throughput utilizing tools like TensorRT, OpenVINO, DeepStream, or ONNX Runtime.
Automated MLOps & Dataset Workflows: Build scalable training, benchmarking, dataset annotation, and active learning loops across edge and cloud deployment setups.
Complex Event Processing: Formulate temporal and spatial logic rules to process multiple video detections, filter out false positives, and yield reliable real-world business insights.
Evaluation Metrics: Ability to benchmark vision performance using metrics like Precision, Recall, F1, mAP, IoU, MOTA, and Frame Rate (FPS) alongside CPU/GPU resource monitoring.
Engineering Fundamentals: Proficiency with Git version control, unit testing, debugging, and handling video streaming protocols (RTSP, HLS).
4. How to Apply
Go to the official HCLTech Careers portal ([www.hcltech.com/careers](https://www.hcltech.com/careers)).
Search for Campus-Trainee (Computer Vision Engineer II) – Chennai.
Complete the online application profile, attach your resume highlighting relevant academic projects, internships, or GitHub repositories, and submit your profile.