Description

You will design, develop, and deploy scalable AI/ML and Generative AI solutions for enterprise applications.

This role is remote.

Responsibilities

• Build and implement Retrieval-Augmented Generation (RAG) pipelines and semantic search systems using embeddings and vector databases.
• Integrate Large Language Models (LLMs) from providers like OpenAI and Anthropic into backend applications.
• Develop scalable ML pipelines for training, evaluation, and deployment, including data preprocessing and feature engineering.
• Build and maintain APIs and microservices using FastAPI or Flask, ensuring robust backend systems.
• Deploy solutions on cloud platforms (AWS, Azure, or GCP) and implement MLOps practices such as CI/CD, monitoring, and model versioning.

Required Skills

• 5+ years of experience in Python programming.
• Hands-on experience with machine learning frameworks: PyTorch, TensorFlow, and scikit-learn.
• Strong understanding of Generative AI, LLMs, and LangChain.
• Practical experience with RAG architectures, NLP, embeddings, and vector search (FAISS, Pinecone).
• Proficiency in API development and backend systems.
• Experience with databases: PostgreSQL, Redis, and general SQL/NoSQL.
• Familiarity with containerization (Docker) and orchestration (Kubernetes).
• Experience deploying on AWS, Azure, or GCP.

Preferred Skills

• Experience with LLM fine-tuning, embedding optimization, and evaluation metrics (Precision@K, MRR, nDCG).
• Familiarity with data pipelines using Airflow, Kafka, or Spark.

Key Skills

Education

Any Graduate