Infosys
Website:
infosys.com
Job details:
Job Title: Lead Analyst, Computer Vision
Job Overview:
As a Lead Computer Vision Engineer, you will lead the development and deployment of cutting-edge computer vision models and solutions for a variety of applications including image classification, object detection, segmentation, and more. You will work closely with cross-functional teams to implement advanced computer vision algorithms, ensure the integration of AI solutions into products, and help guide the research and innovation of next-generation visual AI technologies.
Key Responsibilities:
- Leadership and Team Management:
- Lead a team of computer vision engineers, providing mentorship and guidance in both technical and career development.
- Oversee the execution of computer vision projects from conceptualization through development and deployment.
- Collaborate with product managers, data scientists, and engineers to define project objectives and ensure alignment with business goals.
- Allocate resources effectively across different tasks, ensuring efficient project delivery.
- Research and Development:
- Stay up-to-date with the latest advancements in computer vision, deep learning, and AI, and apply this knowledge to push the boundaries of current solutions.
- Conduct research to advance the field of computer vision, including contributing to the development of new algorithms, frameworks, or methodologies.
- Design and implement novel computer vision models and algorithms for tasks such as object detection, image segmentation, optical character recognition (OCR), and facial recognition.
- Utilize large datasets to train, test, and improve models, optimizing for both performance and efficiency.
- Model Development and Deployment:
- Develop end-to-end computer vision pipelines, from data acquisition and preprocessing to model training, testing, and deployment.
- Optimize models for both accuracy and real-time performance, leveraging tools such as TensorFlow, PyTorch, and OpenCV.
- Work with cloud and edge platforms to deploy models, ensuring scalability and robustness of solutions.
- Collaboration and Cross-Functional Integration:
- Collaborate with software engineering teams to ensure smooth integration of computer vision models into applications and systems.
- Coordinate with data engineers to ensure proper data collection, labeling, and processing workflows.
- Work closely with the QA team to ensure the robustness and correctness of models before deployment.
- Mentorship and Knowledge Sharing:
- Mentor junior engineers, fostering a culture of learning and continuous improvement within the team.
- Provide technical leadership by reviewing code, providing constructive feedback, and setting best practices for development.
- Lead or participate in technical discussions, workshops, and research papers within the company and at external conferences.
- Performance Monitoring and Continuous Improvement:
- Monitor model performance and make improvements where necessary to maintain high accuracy and efficiency.
- Implement continuous learning strategies to keep models updated with new data and evolving requirements.
- Ensure the quality and scalability of computer vision solutions in production.
Skills and Qualifications:
- Educational Background:
- Bachelor's or Master’s degree in Computer Science, Electrical Engineering, Data Science, AI, or a related field. A PhD is a plus.
- Technical Skills:
- Deep Learning Frameworks: Proficiency in TensorFlow, PyTorch, or other deep learning libraries.
- Computer Vision Tools: Expertise in OpenCV, Dlib, and other image processing libraries.
- Model Deployment: Experience deploying models to production using platforms such as AWS, Google Cloud, or NVIDIA Jetson (for edge devices).
- Algorithms: Strong understanding of core computer vision techniques like image classification, object detection (YOLO, Faster R-CNN), image segmentation (U-Net), and feature extraction.
- Programming Languages: Proficient in Python, C++, and other relevant programming languages for computer vision tasks.
- Data Handling: Experience working with large datasets, data augmentation, and preprocessing techniques.
- Optimization: Skills in model optimization techniques such as pruning, quantization, and hardware acceleration (e.g., using GPUs or TPUs).
- Leadership and Communication:
- Strong leadership skills with the ability to inspire, mentor, and lead a team of engineers.
- Excellent communication skills, both written and verbal, with the ability to explain complex technical concepts to non-technical stakeholders.
- Proven ability to manage multiple projects simultaneously and meet deadlines in a fast-paced environment.
- Experience:
- At least 10+ years of hands-on experience in computer vision and deep learning.
- Experience in leading or managing a team of engineers, preferably in a computer vision-related field.
- Proven track record of successful project delivery and deployment of computer vision models in production environments.
- Experience with version control systems (e.g., Git) and collaborative software development practices.
- Preferred Skills:
- Experience with state-of-the-art computer vision techniques like GANs, reinforcement learning for vision tasks, and self-supervised learning.
- Familiarity with edge-computing frameworks (e.g., TensorRT, NVIDIA DeepStream) for deploying models on embedded systems.
- Contributions to open-source projects or published research papers in computer vision or related fields.
Desired Personal Traits:
- Problem-Solving: A strong analytical mindset with the ability to solve complex technical challenges.
- Adaptability: Willingness to learn new technologies and adapt to a rapidly evolving field.
- Innovation: A passion for staying ahead of the curve in AI and computer vision advancements, and a drive for continuous improvement.
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