Senior AI/ML Engineer

We are seeking a highly skilled Senior AI/ML Engineer with deep expertise in Python programming, LLMs, and Generative AI ecosystems. The ideal candidate will have strong fundamentals in machine learning, deep learning, and a solid understanding of modern AI pipelines involving RAG (Retrieval-Augmented Generation), LangChain/LangGraph, document ingestion, and vector databases.

This role requires both hands-on technical expertise and strong programming discipline, with the ability to design, build, and deploy scalable AI solutions that integrate structured and unstructured data sources into real-world intelligent applications.

Roles and Responsibilities

· Design, train, and fine-tune Large Language Models (LLMs) for domain-specific applications.

· Implement Retrieval-Augmented Generation (RAG) pipelines for context-aware responses using enterprise data.

· Work with LangChain, LangGraph, and similar frameworks to build modular, production-ready AI workflows.

· Develop efficient document ingestion and vectorization pipelines to index, embed, and query knowledge bases using vector databases like Pinecone, FAISS, or Chroma.

AI/ML Engineering & Programming Excellence

· Write high-quality, modular, and maintainable code in Python, applying strong software engineering principles.

· Build and optimize data pipelines for feature extraction, preprocessing, and model training.

· Apply deep learning and machine learning concepts for both traditional and generative use cases.

· Implement prompt engineering and context optimization strategies to enhance LLM performance.

MLOps & Deployment

· Develop end-to-end AI workflows with CI/CD, Docker, and Kubernetes.

· Deploy models on cloud platforms (GCP Vertex AI, AWS SageMaker, Azure ML).

· Monitor and optimize performance of deployed models, ensuring scalability and reliability.

Collaboration & Innovation

· Collaborate with cross-functional teams to identify business use cases for AI solutions.

· Research emerging LLM techniques, retrieval strategies, and framework advancements.

· Mentor team members on Python best practices, AI pipeline design, and vector database integration.

Primary Skills:

· Expert-level Python programming skills with solid understanding of algorithms, data structures, and OOP.

· Strong understanding of LLMs (Large Language Models) and transformer-based architectures.

· Hands-on experience with LangChain, LangGraph, and other LLM orchestration frameworks.

· Proficiency in RAG (Retrieval-Augmented Generation) design and implementation.

· Experience in document ingestion, data embedding, and vector database management (FAISS, Pinecone, Chroma, Weaviate).

· Strong grounding in Deep Learning, Machine Learning, and Generative AI.

· Familiarity with TensorFlow, PyTorch, and Hugging Face ecosystems.

· Experience in MLOps, Docker, Kubernetes, and CI/CD pipelines for AI model deployment.

· Strong knowledge of mathematical foundations — linear algebra, probability, statistics.

· Experience with cloud AI platforms (GCP Vertex AI, AWS SageMaker, Azure ML).

Secondary Skills:

· Experience with Big Data frameworks (Hadoop, PySpark) for large-scale data processing.

· Exposure to Kafka for real-time streaming data pipelines.

· Knowledge of time-series forecasting techniques and applications.

· Knowledge of API development for AI model serving (FastAPI, Flask).

· Experience in multi-modal learning (combining text, images, video, or speech)