AI / ML Engineer

The core responsibilities for the job include the following:
Core ML and Engineering:
Write clean, efficient, and well-documented Python code following OOP principles (encapsulation, inheritance, polymorphism, abstraction).
Build and manage end-to-end ML pipelines: data ingestion, preprocessing, model training, evaluation, and deployment.
Develop scalable ML systems using frameworks like PyTorch, TensorFlow, and Scikit-learn.
Generative AI (GenAI) and LLM Systems:
Design and implement LLM-based applications (chatbots, copilots, automation tools).
Build and optimize RAG pipelines using vector databases (e. g., FAISS, Pinecone, Weaviate).
Develop agentic workflows using frameworks like LangChain, LlamaIndex, or similar.
Implement prompt engineering, structured output generation, and tool/function calling.
Fine-tune or optimize LLMs using techniques like LoRA, QLoRA, or instruction tuning.
Work with open-source and proprietary LLMs (e. g., LLaMA, Mistral, GPT, Qwen).
Software Design and Architecture:
Design modular, scalable, and maintainable ML and GenAI systems.
Build APIs and microservices for model serving and GenAI applications.
Contribute to architectural decisions for AI platforms and products.
Data Engineering for AI:
Build data pipelines for feature engineering, transformation, and dataset versioning.
Manage structured and unstructured data (documents, embeddings, logs).
MLOps and LLMOps:
Implement CI/CD pipelines for ML and GenAI systems.
Manage model and prompt versioning, experiment tracking, and reproducibility.
Requirements:
Bachelor's or Master's degree in Computer Science, AI, ML, Data Science, or a related field.
5 years of experience in AI/ML engineering, with 2-3 years in a lead role.
Strong expertise in Python, system design, and scalable AI/ML architecture.
Hands-on experience with TensorFlow, PyTorch, and Scikit-learn.
Strong knowledge of NLP, Computer Vision, Generative AI, LLMs, and deep learning models.
Experience with Docker, Kubernetes, MLOps, CI/CD, and cloud platforms like Amazon Web Services, Google Cloud Platform, or Microsoft Azure.
Strong leadership, stakeholder management, and team mentoring skills.

Experience
5-8 yrs