Campus-Trainee

Candidates typically go through a structured interview process at HCL Technologies. The first round focuses on coding and data structures, followed by a technical round covering computer vision concepts, system design, and MLOps. The final HR round assesses cultural fit and communication skills. Questions often revolve around real‑world vision problems, algorithm optimization, and project experience.

HCL Technologies fosters a collaborative and inclusive work environment where employees are encouraged to innovate and take ownership of projects. The company emphasizes continuous learning through internal training programs and offers a good work‑life balance with flexible work arrangements.

Bachelor’s degree in Computer Science, Electronics, Electrical, Mechanical or related engineering discipline. Minimum 60% or 6.5 CGPA. Fresh graduates or those with up to 1 year of experience. No backlogs allowed. Strong academic record in mathematics, physics, and programming is preferred.

Round 1: Technical interview – coding and computer vision concepts → Round 2: Technical interview – system design and MLOps → Round 3: HR interview

HCL Technologies is a global technology powerhouse with over 223,000 employees across 60 countries. The company delivers cutting‑edge solutions in digital, engineering, cloud, and AI, serving a diverse portfolio of industries such as finance, manufacturing, healthcare, telecom, and retail. With a consolidated revenue of $14.8 billion in the last fiscal year, HCL Technologies is known for its innovation, customer‑centric approach, and a culture that nurtures talent and promotes continuous learning. The Campus‑Trainee program is designed to launch the careers of fresh graduates into the world of computer vision and AI. As a Computer Vision Engineer II – Vision Model Development & Automation, you will build production‑ready pipelines that power surveillance, industrial automation, and smart spaces. Your work will span the entire model lifecycle: from data ingestion and pre‑processing to inference, post‑processing, and deployment on edge and cloud platforms. You will also create automated MLOps pipelines, optimize models for latency using TensorRT or OpenVINO, and develop logic for complex event processing. Key responsibilities include: 1. Designing and implementing end‑to‑end computer vision pipelines for tasks such as object detection, tracking, re‑identification, segmentation, anomaly detection, and OCR. 2. Fine‑tuning state‑of‑the‑art models (YOLO, SSD, Faster R‑CNN, EfficientNet) and integrating them into scalable platforms. 3. Building automated training and evaluation pipelines that support continuous model updates and benchmarking. 4. Optimizing models for real‑time performance using tools like TensorRT, OpenVINO, DeepStream, or ONNX Runtime. 5. Developing robust event‑processing logic to correlate detections, apply spatial/temporal rules, and filter noise. 6. Creating dataset management utilities for annotation, quality checks, synthetic data generation, and active learning. 7. Troubleshooting vision performance issues under varied lighting, occlusion, and camera angles. 8. Documenting architecture, interfaces, benchmarks, and deployment guides for internal and external stakeholders. 9. Collaborating with platform engineers to ensure seamless integration and deployment. 10. Staying updated with the latest research and industry trends in computer vision. Tech stack: Python, C++, OpenCV, NumPy, PyTorch/TensorFlow, ONNX, TensorRT, OpenVINO, DeepStream, Git, Docker, CI/CD tools. Growth path: Starting as a campus trainee, you can progress to a full‑time Computer Vision Engineer, then to Senior Engineer, Lead Engineer, and eventually to a Technical Lead or Manager role within the AI & Automation domain. Why join HCL Technologies? The company offers a collaborative environment, exposure to global clients, and a strong focus on skill development. With a culture that values innovation, work‑life balance, and continuous learning, HCL provides ample opportunities to grow both technically and professionally. This role is ideal for fresh graduates who are passionate about computer vision, enjoy problem‑solving, and want to work on real‑world applications that impact millions of users.