- Design, build, and deploy Machine Learning (ML) and Artificial Intelligence (AI) models.
- Develop end-to-end ML pipelines for data ingestion, preprocessing, training, validation, and deployment.
- Implement supervised, unsupervised, and reinforcement learning algorithms.
- Build and optimize NLP, Computer Vision, and Generative AI solutions.
- Train, fine-tune, and evaluate deep learning models using large datasets.
- Deploy ML models using MLOps best practices.
- Monitor model performance and retrain models as needed.
- Collaborate with cross-functional teams to identify AI opportunities and deliver business solutions.
- Develop APIs and scalable AI applications for production environments.
- Ensure data quality, security, and governance standards are maintained.
Required Skills
- Robust programming experience in Python.
- Hands-on experience with:
- Machine Learning Algorithms
- Deep Learning
- Natural Language Processing (NLP)
- Computer Vision
- Generative AI / LLMs
- Experience with ML frameworks
- TensorFlow
- PyTorch
- Scikit-learn
- Keras
- Knowledge of data processing tools:
- Pandas
- NumPy
- PySpark
- Experience with Vector Databases
- Pinecone
- FAISS
- ChromaDB
- Hands-on experience with LLMs:
- OpenAI
- Azure OpenAI
- Gemini
- Claude
- Hugging Face
- Experience in prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning techniques.
- Knowledge of REST APIs and microservices architecture.
- Experience with Git, CI/CD, and software development best practices.