HCLTech is a global technology powerhouse with more than 223,000 employees spread across 60 countries. The company delivers end‑to‑end digital, engineering, cloud and AI services to a wide spectrum of industries, ranging from financial services and manufacturing to healthcare, telecom and retail. With a revenue of $14.8 billion for the fiscal year ending June 2026, HCLTech is known for its "Employees First" philosophy, which places a strong emphasis on continuous learning, innovation and work‑life balance. The firm’s culture encourages fresh talent to take ownership early, experiment with emerging technologies and contribute to real‑world solutions for Fortune‑500 clients. The Campus‑Trainee role is positioned as a Computer Vision Engineer II focused on Vision Model Development & Automation. It is tailored for Tier‑1 fresh graduates (or candidates with up to one year of experience) who have a solid grounding in computer‑vision fundamentals and a passion for building production‑ready pipelines. The trainee will work on end‑to‑end vision solutions that power surveillance, industrial automation and smart‑space applications, collaborating closely with platform engineers, data scientists and product managers. Key responsibilities include: 1. Designing and integrating complete vision pipelines—from image/video ingestion to preprocessing, inference, post‑processing and metadata generation. 2. Implementing and fine‑tuning state‑of‑the‑art algorithms for object detection, tracking, re‑identification, segmentation, anomaly detection and OCR. 3. Building automated MLOps workflows for model training, evaluation, benchmarking and deployment on edge and cloud environments. 4. Optimising models for latency and throughput using TensorRT, OpenVINO, DeepStream or ONNX Runtime. 5. Developing complex event‑processing logic to correlate detections, apply temporal/spatial rules and filter false positives. 6. Creating tools for dataset management, automated annotation, quality checks, synthetic data generation and active‑learning loops. 7. Troubleshooting performance issues arising from lighting, occlusion or camera angles and delivering algorithmic or data‑centric fixes. 8. Documenting pipeline architecture, model interfaces, performance benchmarks and deployment guides for internal and external stakeholders. The tech stack revolves around C++/Python, OpenCV, NumPy, PyTorch/TensorFlow, video codecs (H.264/H.265), streaming protocols (RTSP, HLS) and version‑control tools like Git. Trainees will gain exposure to MLOps platforms, containerisation (Docker/Kubernetes) and edge‑deployment frameworks, setting a strong foundation for a career in AI‑driven product engineering. Growth paths typically lead to senior vision engineer, AI architect or product lead roles within 2‑4 years, backed by HCLTech’s robust learning ecosystem and internal mobility programs. Joining HCLTech offers the chance to work on cutting‑edge vision problems, receive mentorship from industry veterans, and be part of a company that values innovation, diversity and employee well‑being.