Sr. AI/ML Engineer

Key Responsibilities: Agentic AI Development: Work on building scalable multi-modal Large Language Model (LLM) based AI agents, leveraging frameworks such as LangGraph, Microsoft Autogen, or Crewai. AI Research and Innovation: Research and build innovative solutions to relevant AI problems, including Retrieval-Augmented Generation (RAG), semantic search, knowledge representation, tool usage, fine-tuning, and reasoning in LLMs. Technical Expertise: Proficiency in a technology stack that includes Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, and React. LLM and NLP Experience: Hands-on experience working with LLMs, RAG architectures, Natural Language Processing (NLP), or applying Machine Learning to solve real-world problems. Dataset Development: Strong track record of building datasets for training and/or evaluating machine learning models. Customer Focus: Enjoy diving deep into the domain, understanding the problem, and focusing on delivering value to the customer. Adaptability: Thrive in a fast-paced environment and are excited about joining an early-stage venture. Model Deployment and Management: Automate model deployment, monitoring, and retraining processes. Collaboration and Optimization: Collaborate with data scientists to review, refactor, and optimize machine learning code. Version Control and Governance: Implement version control and governance for models and data. Required Qualifications: Bachelor's degree in computer science, Software Engineering, or a related field 5-8 years of experience in MLOps, DevOps, or related roles Have strong programming experience and familiarity with Python based deep learning frameworks like Pytorch, JAX, Tensorflow Have strong familiarity and knowledge of machine learning concepts Proficiency in cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools like Terraform Desired Skills: Experience with experiment tracking and model versioning tools. You have experience with technology stack: Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQL Alchemy, Alembic, OpenAI, Docker, Azure, Typescript, React. Knowledge of data pipeline orchestration tools like Apache Airflow or Prefect Familiarity with software testing and test automation practices Understanding of ethical considerations in machine learning deployments Strong problem-solving skills and ability to work in a fast-paced environment