AI/ML Team Lead

Job Title: AI/ML Team Lead

Location:

About the Role

AI/ML Team Lead

Key Responsibilities

• Lead and manage

  a team of ML engineers and data scientists, providing technical guidance and mentorship.
• Architect and implement advanced

  Computer Vision models

  for tasks such as image classification, object detection, segmentation, OCR, video analytics, etc.
• Collaborate cross-functionally with product managers, software engineers, and stakeholders to translate business problems into ML solutions.
• Own the

  full ML lifecycle

  from data collection and pre-processing to model training, evaluation, deployment, and monitoring.
• Develop

  production-quality Python code

  and collaborate on scalable and maintainable ML pipelines.
• Stay updated with the latest research and trends in computer vision and machine learning; evaluate and integrate new technologies.
• Ensure robust testing, documentation, and model explainability for compliance and reproducibility.
• Promote best practices for ML Ops, version control, and continuous integration/continuous deployment (CI/CD).

Requirements

Must-Have:

• Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, or related field.
• 4 to 6 years of hands-on experience in AI/ML, with team leadership or technical lead role.
• Strong expertise in

  Computer Vision

  techniques and frameworks (e.g., OpenCV, PyTorch, TensorFlow, Streamlit, Detectron2, YOLO, etc.).
• Excellent proficiency in

  Python

  and ML libraries (NumPy, scikit-learn, pandas, etc.).
• Proven experience in deploying models to production environments (REST APIs, microservices, containers).
• Solid understanding of

  ML Ops practices

  , including model versioning, monitoring, and reproducibility.
• Strong problem-solving, communication, and leadership skills.

Nice-to-Have:

• Experience with cloud platforms (AWS, GCP, Azure) and tools like Docker, Kubernetes, Airflow, or MLflow.
• Familiarity with edge AI or real-time computer vision applications.
• Contributions to open-source projects or research publications in relevant fields.