Description

You will design, build, and deploy AI solutions using GenAI, LLMs, and traditional machine learning techniques. You own the end-to-end lifecycle from data processing to model deployment and monitoring.

Responsibilities

• Develop and maintain AI/LLM applications using Python, PyTorch, TensorFlow, and frameworks like LangChain and Hugging Face.
• Implement MLOps and LLMOps pipelines using MLflow, Docker, Kubernetes, and Git CI/CD to ensure reliable model delivery.
• Build and optimize data processing workflows using PySpark, SQL, and DataBricks for efficient data lake operations.
• Deploy scalable microservices and APIs using FastAPI, Flask, and Streamlit, integrating with cloud AI platforms.
• Collaborate on agile projects, managing priorities across multiple initiatives while adhering to AI ethics and compliance standards.

Required Skills

• 5+ years of experience in AI, data science, or machine learning projects.
• Proficiency in Python, PyTorch, TensorFlow, Scikit-Learn, and PySpark.
• Hands-on experience with LLM frameworks (LangChain, LangGraph) and models (OpenAI GPT, Gemini, LLaMA).
• Strong understanding of MLOps tools: MLflow, Docker, Kubernetes, Git CI/CD.
• Experience with cloud AI platforms: AWS (SageMaker, S3), Azure (AI, Cognitive Search), or Google Cloud (Vertex AI).
• Proficiency in SQL and data engineering principles.
• Bachelor’s degree in Computer Science, AI, Data Science, or a related field.

Key Skills

Education

Bachelor's degree