Design, develop, and deploy end-to-end AI/ML solutions from data ingestion to production.

Build and optimize ML/DL models for NLP, computer vision, recommendation systems, and predictive analytics.

Implement and maintain MLOps pipelines (CI/CD for ML) for scalable deployment and monitoring.

Collaborate with cross-functional teams (data scientists, engineers, product managers) to define AI-driven solutions.

Research and integrate Generative AI (LLMs, diffusion models, transformers) into real-world applications.

Drive data strategy, including data collection, preprocessing, and feature engineering.

Optimize models for performance, scalability, and cost-effectiveness in cloud/on-prem environments.

Mentor junior engineers and contribute to best practices in AI development.

Required Skills & Qualifications:

Strong proficiency in Python and AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, Hugging Face).

Hands-on experience with NLP (LLMs, transformers, embeddings, vector databases).

Deep understanding of neural networks, reinforcement learning, and generative models.

Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes).

Strong knowledge of SQL/NoSQL databases and data engineering practices.

Soft Skills: Excellent problem-solving, communication, and leadership abilities.