284 Computer Vision jobs in Chennai

Role Overview:

Eternal Robotics is seeking a seasoned Computer Vision Engineer with a profound capability to lead and innovate within our technology team. The individual will play a pivotal role in propelling our computer vision projects by leveraging extensive technical skills, leading teams, and ensuring optimal integration of computer vision technologies within web platforms and cloud environments.

Job Purpose:

The Computer Vision Engineer will sculpt the future of Eternal Robotics technological landscape by developing, implementing, and optimizing advanced computer vision algorithms and models, and ensuring their seamless deployment in production environments both on-premises and on the cloud.

Key Responsibilities:

• Strategic Leadership and Project Management:
• Spearhead the computer vision projects, ensuring consistent alignment with organizational objectives and technological advancements.
• Manage end-to-end computer vision projects, ensuring on-time delivery, scalability, and robustness of implemented solutions.
• Technical Development and Innovation:
• Develop and optimize computer vision algorithms using technologies like OpenCV, DeepStream, and Python, ensuring they meet the top-notch standards for accuracy and efficiency.
• Innovate and research new methodologies and technologies that propel forward the capabilities of the computer vision team.
• Web Development and Integration:
• Ensure the seamless integration of computer vision solutions within web platforms, enhancing user experiences and functionality.
• Coordinate with web development teams, providing them with necessary APIs and technical support for integration.
• Cloud Computing and On-Premises Management:
• Lead the deployment of computer vision solutions in cloud environments (AWS expertise is preferable) and on-premises, ensuring security and compliance are maintained.
• Develop strategies for storage, retrieval, and computation scalability in cloud environments, ensuring cost-effectiveness and efficiency.
• Team Leadership and Mentorship:
• Foster a conducive environment for knowledge sharing and mentorship, elevating the skills and competencies of the team.
• Conduct regular one-on-ones and team meetings, ensuring alignment, resolving conflicts, and facilitating continuous learning.
• Stakeholder Management and Collaboration:
• Communicate effectively with stakeholders, ensuring requirements are understood and expectations are met.
• Collaborate with cross-functional teams, ensuring synergies between various technological domains within the organization.
• Quality Assurance and Compliance:
• Ensure that the developed algorithms and solutions comply with quality standards and are rigorously tested.
• Establish protocols that adhere to legal and ethical standards in data usage and model implementations.

Qualifications and Experience:

• Educational Qualification:
  Bachelor's/Master's degree in Computer Science, Electrical Engineering, or related field.
• Experience:
  2+ years of proven experience in developing and implementing computer vision algorithms and managing related projects.
• Technical Skills:
  Proficiency in Python, OpenCV, Deepstream, web development technologies, and cloud computing (preferably AWS).
• Leadership:
  Demonstrable experience in leading and mentoring technical teams with a positive track record.

Skills and Abilities:

• Analytical Skills:
  Ability to discern trends and insights from complex data and processes.
• Problem Solving:
  An aptitude for developing innovative solutions to overcome complex technical challenges.
• Communication:
  Excellent verbal and written communication skills for technical and non-technical audiences.
• Team Collaboration:
  Ability to work effectively in and lead cross-functional teams.

Key Performance Indicators

• Project Completion Rate
• Project Quality
• Team Member Development
• Team Productivity
• Algorithm Efficiency
• Algorithm Accuracy
• Integration Success Rate
• System Downtime
• Cross-Team Project Success
• Stakeholder Satisfaction

Job description

Key Responsibilities:

• Develop computer vision solutions for machine learning applications.
• Design deep learning models using frameworks like PyTorch, TensorFlow, and OpenCV.
• Implement algorithms for object detection, segmentation, classification, and tracking.
• Work with large datasets for image processing and develop scalable models.
• Deploy models on edge devices to optimize inference efficiency and resource utilization.
• Collaborate with data scientists to understand project requirements and deliver solutions.
• Implement and evaluate model performance to ensure accuracy and efficiency.

• Stay up to date with the latest techniques in deep learning and classical computer vision

• Implement and evaluate model performance to ensure accuracy and efficiency.

• Stay up to date with the latest techniques in deep learning and classical computer vision

Qualifications:

• Bachelor s degree in Computer Science, or related field.
• 3+ years of experience in computer vision.
• Strong skills in Python and experience with deep learning frameworks like PyTorch and TensorFlow.
• Experience with computer vision libraries such as OpenCV.
• Proficiency in classical computer vision techniques, including SIFT, SURF, feature extraction, image manipulation, and calibration.
• Experience in deploying models to edge devices for real-time computer vision applications.
• Strong understanding of Data Structures and Algorithms (DSA) with hands-on coding experience.
• Strong experience working with large-scale datasets.
• Excellent communication and collaboration skills.

• Design, develop, and implement state-of-the-art machine learning models for computer vision tasks.
• Build and maintain robust ML pipelines for data preprocessing, model training, evaluation, and deployment.
• Collaborate with software engineers and product managers to integrate ML models into production systems.
• Conduct research on new computer vision algorithms and techniques, staying at the forefront of the field.
• Optimize model performance for efficiency, accuracy, and scalability across different hardware platforms.
• Analyze large datasets of images and videos to identify patterns and inform model development.
• Experiment with various deep learning frameworks (e.g., PyTorch, TensorFlow) and libraries.
• Develop strategies for data augmentation, model regularization, and hyperparameter tuning.
• Troubleshoot and debug complex ML systems and deployments.
• Mentor junior engineers and share expertise on computer vision and ML best practices.
• Document research findings, model architectures, and implementation details.
• Present technical solutions and project progress to cross-functional teams.

• Master's or Ph.D. in Computer Science, Machine Learning, Electrical Engineering, or a related field.
• 5+ years of professional experience in machine learning engineering, with a strong focus on computer vision.
• Proven experience in developing and deploying deep learning models for tasks like object detection, image classification, segmentation, and generation.
• Proficiency in Python and experience with ML libraries such as TensorFlow, PyTorch, Keras, OpenCV, and scikit-learn.
• Solid understanding of computer vision principles, image processing, and deep learning architectures (CNNs, Transformers, GANs).
• Experience with cloud ML platforms (e.g., AWS SageMaker, Google AI Platform, Azure ML).
• Familiarity with MLOps principles and tools for model lifecycle management.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills, suitable for a remote work environment.

Job Title:
Computer vision Engineer

Location:
Chennai, India

Employment Type:
Full-Time

Reports To:
CMD ( later to the CTO)

Job Overview

As our AI/ML Engineer, you will be responsible for designing and prototyping the core machine learning architectures that drive our solution. You will collaborate directly with the founder to brainstorm, evaluate, and select the best approaches for computer vision, sensor fusion, and reinforcement learning applications in cricket and badminton.

Given that this is a new domain, candidates with experience in adjacent areas (such as robotics, autonomous systems, sports analytics, surveillance, or IoT) are encouraged to apply. We value innovative problem solvers who can adapt their skills to meet our unique challenges.

Key Responsibilities

• Architecture & Design:
• Propose and evaluate multiple AI/ML architectures suitable for real-time officiating tasks (object detection, event detection, trajectory prediction, and sensor fusion).
• Collaborate with the founder to select and iterate on the optimal architecture for our use case.
• Algorithm Development:
• Develop computer vision algorithms to detect and track critical objects (e.g., sports balls, players, court lines).
• Design and implement reinforcement learning (RL) models for dynamic PTZ camera control (tracking, panning, and zooming) to ensure the best camera viewpoints.
• Build predictive models for real-time decision-making (e.g., anticipating ball trajectories for no-ball calls, scoring events).
• Sensor Fusion:
• Integrate data from video feeds with auxiliary sensors (audio, IR, radar, etc.) to improve the accuracy and reliability of event detection.
• Optimize models for low-latency performance on edge devices.
• Prototyping & Testing:
• Rapidly prototype and validate AI/ML modules using real or simulated data.
• Work closely with the full-stack developer to integrate AI components into the broader software system.
• Documentation & Research:
• Document architecture decisions, model designs, and implementation details.
• Stay updated on recent research and advancements in computer vision, machine learning, and reinforcement learning, and apply relevant innovations to enhance the product.
• Collaboration:
• Participate in brainstorming sessions and technical reviews with the product management and development teams.
• Provide insights on potential improvements and scalability for the system as we expand from a prototype to a full-scale commercial product.

Qualifications & Skill Sets

Educational Qualifications:

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related discipline with a focus on machine learning, computer vision, robotics, or data science.

Technical Skills:

• Programming Languages:
  Proficiency in Python and familiarity with C++.
• Deep Learning Frameworks:
  Experience with TensorFlow, PyTorch, or similar frameworks.
• Computer Vision:
  Hands-on experience with OpenCV, YOLO, or other object detection and tracking libraries; strong knowledge of convolutional neural networks (CNNs).
• Reinforcement Learning:
  Understanding of RL concepts and experience with frameworks such as Open AI Gym or similar; ability to prototype RL solutions for real-time control.
• Sensor Fusion:
  Familiarity with techniques to integrate and process multi-modal data (video, audio, IR, radar, etc.).
• Optimization for Real-Time Systems:
  Experience in tuning models and algorithms for low-latency, edge, or embedded deployment.
• Software Engineering:
  Ability to write clean, well-documented code and collaborate using version control systems (e.g., Git).

Domain-Relevant Experience:

• While direct experience in sports officiating is not required, experience in adjacent fields such as:
• Sports Analytics:
  Building models for performance analysis or event detection in sports.
• Robotics/Autonomous Systems:
  Developing vision and control algorithms for real-time decision-making.
• Surveillance/IoT:
  Implementing sensor fusion techniques and real-time video analytics.
• Project or research experience that demonstrates your ability to solve complex problems in real-time environments is highly desirable.

Soft Skills:

• Problem-Solving:
  Ability to work through challenging technical problems and innovate solutions.
• Collaboration:
  Excellent communication skills to articulate technical concepts to non-technical stakeholders and work effectively in a small, cross-functional team.
• Adaptability:
  Self-motivated and eager to learn new domains, with a proactive approach to overcoming technical challenges.
• Team Spirit:
  A willingness to contribute ideas, accept feedback, and continuously iterate on solutions.

Why Join Us?

• Innovative Domain:
  Be at the forefront of merging AI with sports officiating and analytics—a field ripe for innovation.
• Collaborative Environment:
  Work directly with the founder and a lean, agile team, where your ideas directly influence the product's direction.
• Growth Opportunity:
  Gain experience in building a product from concept to market, with room to grow as the company scales.
• Competitive Compensation:
  We offer a competitive salary with potential equity participation in a rapidly evolving startup.

• Conducting cutting-edge research in computer vision and deep learning.
• Developing and implementing novel algorithms for image and video understanding.
• Designing, training, and evaluating deep neural networks for various vision tasks.
• Collaborating with other researchers and engineers on complex AI projects.
• Publishing research findings in top-tier academic venues (conferences and journals).
• Contributing to the development of robust and scalable AI models and systems.
• Staying abreast of the latest advancements in AI, machine learning, and computer vision.
• Mentoring junior researchers and contributing to the team's knowledge base.
• Exploring new research directions and identifying potential application areas for AI technologies.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field with a strong focus on computer vision.
• Proven track record of research excellence, evidenced by publications in reputable conferences (e.g., CVPR, ICCV, ECCV) and journals.
• Extensive experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Strong programming skills in Python and proficiency with libraries like NumPy, SciPy, and OpenCV.
• Deep understanding of various computer vision algorithms and techniques.
• Experience with large-scale datasets and distributed training is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration abilities, with the capacity to articulate complex technical concepts clearly.
• Ability to work independently and manage research projects effectively in a remote setting.