Key Responsibilities
- Design, develop, and deploy machine learning models for business applications.
- Collect, clean, preprocess, and analyze structured and unstructured data.
- Build and optimize supervised and unsupervised machine learning models.
- Perform feature engineering and model selection.
- Train, evaluate, and fine-tune ML models using appropriate performance metrics.
- Develop data pipelines for model training and inference.
- Deploy machine learning models into production environments.
- Monitor model performance and improve models based on new data.
- Work with data scientists, software engineers, and business teams.
- Conduct experiments and document model performance and results.
- Implement scalable and maintainable AI/ML solutions.
- Stay updated with emerging AI/ML technologies and research.
Required Technical Skills
- Python
- Strong understanding of Machine Learning concepts and algorithms
- NumPy, Pandas, Scikit-learn
- Data preprocessing and feature engineering
- Model evaluation and validation
- SQL and database fundamentals
- Git/GitHub
- Basic understanding of statistics and probability
- Experience with ML frameworks such as TensorFlow or PyTorch
Deep Learning Skills
- Neural networks and deep learning fundamentals
- CNNs and RNNs
- Transfer learning
- Model optimization and fine-tuning
- Familiarity with GPU-based model training
Generative AI / LLM Skills
- Understanding of Generative AI and Large Language Models (LLMs)
- Prompt engineering
- Embeddings and vector databases
- Retrieval-Augmented Generation (RAG)
- Familiarity with transformer architectures
- Experience with LLM APIs and/or open-source models
- Basic understanding of AI agents and tool calling
MLOps & Deployment Skills
- Model deployment using FastAPI, Flask, or similar frameworks
- Docker and containerization
- CI/CD fundamentals
- Cloud platforms such as AWS, Azure, or Google Cloud
- Model monitoring and versioning
- Familiarity with MLflow or similar MLOps tools
- Understanding of REST APIs and microservices
Preferred Skills
- NLP and computer vision
- Time-series forecasting
- Hugging Face Transformers
- LangChain or similar AI frameworks
- Vector databases such as FAISS, Pinecone, or similar technologies
- Kubernetes
- Spark or other distributed data-processing technologies
