0 years

6 Lacs

Posted:1 day ago| Platform: GlassDoor logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Key Responsibilities:

  • Develop, fine-tune, and deploy LLM-based NLP models for tasks such as text classification, summarization, entity recognition, and question answering.
  • Implement deep learning architectures using TensorFlow and/or PyTorch.
  • Integrate OpenAI APIs and other foundation models into internal applications and tools.
  • Design and build computer vision models for image detection, recognition, classification, and segmentation.
  • Collaborate with cross-functional teams including product managers, data engineers, and UI/UX designers.
  • Stay updated with the latest research trends in AI/ML and apply them to enhance system capabilities.
  • Optimize model performance for scalability, accuracy, and speed.
  • Build pipelines for data preprocessing, model training, validation, and deployment.
  • Document models, experiments, and system behavior for team knowledge sharing.

Key Skills & Qualifications:

  • Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Strong hands-on experience with TensorFlow (or PyTorch).
  • Deep understanding of NLP techniques, transformers, BERT, GPT, T5, etc.
  • Experience working with OpenAI, Hugging Face, or other LLM frameworks.
  • Solid foundation in Computer Vision concepts and frameworks like OpenCV, YOLO, CNNs, Detectron, etc.
  • Proficient in Python and relevant libraries (e.g., Numpy, Pandas, Scikit-learn).
  • Experience with REST APIs, Flask/FastAPI for deploying ML models is a plus.
  • Excellent problem-solving and analytical skills.

Preferred:

  • Prior experience in building AI-based SaaS products or intelligent automation solutions.
  • Knowledge of MLOps, model versioning, and cloud platforms (AWS/GCP/Azure).
  • Familiarity with Reinforcement Learning and Generative AI is a bonus.

Job Type: Full-time

Pay: Up to ₹50,000.00 per month

Schedule:

  • Morning shift

Work Location: In person

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