KASHII UPDATEZ Everyday Student Requirements & Python Coding Tutorials by Python Kashi
KashiiUpdatez
REQUIREMENT_ID_165 β€’ 3-DAY_ACTIVE_POLICY

Computer Vision Engineer II – Vision Model Development & Automation

Company
Company HCLTech
Type
Opportunity Type Internship
Salary
Stipend / Salary 5 LPA
Location
Location Pan India
Posted Date
Posted Date Today
C++ Python OpenCV NumPy PyTorch TensorFlow Object Detection Tracking Segmentation OCR Video Processing TensorRT OpenVINO ONNX Runtime Git Docker Linux MLOps Data Annotation Performance Optimization
πŸ“–
Aptitude Practice Questions Open Resource β†—
Curated quantitative and logical reasoning problems to help you ace the online aptitude round at HCL.
πŸ“–
Technical Interview Preparation Open Resource β†—
Comprehensive guide covering coding patterns, data structures, and computer vision fundamentals for HCL technical interviews.
πŸ“–
Interview Questions & Answers Open Resource β†—
Compilation of frequently asked interview questions and model answers specific to HCL hiring processes.
πŸ“–
Coding Practice Problems Open Resource β†—
A large set of algorithmic problems to sharpen coding skills required for HCL's technical assessment.

B.Tech / B.E. or M.Tech in Computer Science, Information Technology, Electronics & Communication, Electrical Engineering or related fields. Minimum 60% aggregate (or CGPA 6.5/10). Final year students of 2025, 2026 or 2027 batches eligible. No active backlogs at the time of joining. Strong academic record and demonstrable projects/internships in computer vision or deep learning.

1
Round 1: Online Aptitude Test (Logical Reasoning, Quantitative, Verbal)
2
Round 2: Technical Interview (coding in Python/C++, computer vision concepts, DL fundamentals)
3
Round 3: HR Interview (fitment, communication, career aspirations)
HCL Technologies is a leading global IT services company headquartered in Noida, India, with a presence in over 50 countries. The firm helps enterprises across industries accelerate their digital transformation journeys through cloud, AI, cybersecurity, and automation solutions. With a strong focus on innovation, HCL has built several AI and computer‑vision labs that work on cutting‑edge projects ranging from smart surveillance to industrial automation. The company’s culture encourages continuous learning, collaboration across geographies, and rapid career growth for fresh talent. The role of Computer Vision Engineer II – Vision Model Development & Automation is designed for fresh graduates who have a solid grounding in computer‑vision fundamentals and a passion for building production‑grade pipelines. As a member of the Vision AI team, you will translate research‑grade algorithms into scalable services that power real‑world applications such as intelligent surveillance, smart factories, and connected spaces. You will work closely with platform engineers, data scientists, and product managers to ensure that models meet latency, accuracy, and reliability targets. Key Responsibilities: 1. Design, develop, and integrate end‑to‑end vision pipelines covering ingestion, pre‑processing, inference, post‑processing, and metadata generation. 2. Implement and fine‑tune state‑of‑the‑art algorithms for object detection, tracking, re‑identification, segmentation, anomaly detection, and OCR. 3. Build automated MLOps workflows for model training, evaluation, benchmarking, and deployment on edge and cloud platforms. 4. Optimize vision models for latency and throughput using TensorRT, OpenVINO, DeepStream, or ONNX Runtime. 5. Create complex event‑processing logic to correlate detections, apply temporal/spatial rules, and filter false positives. 6. Develop scripts for dataset management, automated annotation, quality checks, synthetic data generation, and active‑learning loops. 7. Diagnose and resolve performance issues arising from lighting variations, occlusions, or camera angles. 8. Document pipeline architecture, model interfaces, performance benchmarks, and deployment guides for internal and external stakeholders. 9. Collaborate with cross‑functional teams to integrate vision services into larger enterprise solutions. 10. Stay updated with the latest research and contribute ideas for new product features. Tech Stack: C++ / Python, OpenCV, NumPy, PyTorch or TensorFlow, TensorRT/OpenVINO/DeepStream, ONNX, Git, Docker, Linux, video codecs (H.264/H.265), streaming protocols (RTSP, HLS). Growth Path: Freshers start as Vision Engineer I, progress to Engineer II, then Senior Engineer, Lead Engineer, and eventually Architecture or Management roles within HCL’s AI/ML practice. Why Join HCL? You will get exposure to large‑scale, real‑world computer‑vision problems, mentorship from industry veterans, and a clear roadmap for technical and leadership growth. The company’s global footprint also opens opportunities for international assignments and cross‑domain projects.

HCLTech β€” QA & Automation Testing Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC πŸ“–
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource β†—
COMPANY GUIDE 🎯
HCLTech Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for HCLTech and off-campus tech roles.

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource β†—
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (C++, Python, OpenCV, NumPy, PyTorch, TensorFlow, Object Detection, Tracking, Segmentation, OCR, Video Processing, TensorRT, OpenVINO, ONNX Runtime, Git, Docker, Linux, MLOps, Data Annotation, Performance Optimization) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
HCLTech Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between Implicit Wait, Explicit Wait, and Fluent Wait in Selenium? Answer β–Ό
Model Answer: Implicit Wait sets a global timeout for all element lookups. Explicit Wait pauses execution until a specific ExpectedCondition (e.g. elementToBeClickable) is met. Fluent Wait allows defining polling frequency and ignoring specific exceptions like NoSuchElementException.
Explain the Page Object Model (POM) and its advantages in Test Automation. Answer β–Ό
Model Answer: POM is a design pattern that creates an object repository for web UI elements. It separates test scripts from page locators, reducing code duplication and making maintenance easy when UI elements change.
How do you handle dynamic WebElements whose ID changes on page reload? Answer β–Ό
Model Answer: Use dynamic XPath methods like contains(), starts-with(), text(), or XPath axes (ancestor, following-sibling, parent) instead of brittle absolute paths.
What is the difference between @BeforeMethod and @BeforeClass in TestNG? Answer β–Ό
Model Answer: @BeforeClass runs once before the first test method in the current class, while @BeforeMethod executes before each individual test method.
How do you validate REST API response codes and JSON payload using Postman / RestAssured? Answer β–Ό
Model Answer: In RestAssured: given().when().get('/endpoint').then().assertThat().statusCode(200).body('status', equalTo('ACTIVE')).
Why do you want to join HCLTech as a Computer Vision Engineer II – Vision Model Development & Automation?
Preparation Tip: Highlight HCLTech's market reputation, recent tech innovations, and how your skills in C++ directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

More Fresh Requirements in Software Engineering

View Category Feed β†—
HCLTech
Computer Vision Engineer II – Vision Model Development & Automation
Apply Apply Now β†—
Chat Chat with Kashii