Data Scientist

Job Description:

Key Responsibilities

• Develop and optimize computer vision models for object detection, segmentation, classification, tracking, OCR, etc.

• Build end-to-end deep learning pipelines from data collection, preprocessing, training, tuning, and deployment.

• Implement advanced image processing techniques for feature extraction and image enhancement.

• Design and train models using CNNs, RNNs, Transformers, Vision Transformers (ViT), GANs, and diffusion models.

• Work on Generative AI applications such as image generation, style transfer, synthetic data creation, and multimodal models.

• Develop scalable machine learning workflows, including model evaluations and experiment tracking.

• Collaborate with cross-functional teams to translate business requirements into technical solutions.

• Deploy ML models into production using MLOps practices and monitor performance.

• Research and integrate the latest advancements in AI, computer vision, and GenAI.

• Prepare documentation, reports, and present insights to stakeholders.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field.

• 5+ years of experience in data science and computer vision.

• Strong expertise in:

  • Deep Learning (PyTorch, TensorFlow, Keras)

  • Computer Vision & Image Processing (OpenCV, PIL, scikit-image)

  • Machine Learning (scikit-learn, XGBoost, LightGBM)

  • Generative AI (GANs, diffusion models, LLM-based multimodal systems)

• Hands-on experience with model deployment (TensorRT, ONNX, Docker, FastAPI).

• Strong programming skills in Python, with good understanding of algorithms and data structures.

• Experience working with cloud platforms (AWS, Azure, GCP).

• Familiarity with MLOps tools (MLflow, DVC, Kubernetes, Git).

• Strong analytical and problem-solving skills with the ability to work independently.