AI/ML Engineer

We’re looking for a passionate AI/ML Engineer with 3+ years of experience who can bridge the gap between machine learning models and production-ready APIs using Node.js and FastAPI.

In this role, you’ll train, fine-tune, and deploy ML models; integrate them with scalable backend systems; and build intelligent, data-driven applications using the latest in GenAI — including Hugging Face, OpenAI, LangChain, and more.

Key Responsibilities

• Design, train, and deploy machine learning and deep learning models for NLP, vision, or recommendation systems.
• Develop robust APIs using Node.js (Express/Nest.js) and Python FastAPI for serving AI/ML models.
• Fine-tune and serve Hugging Face Transformers and LLMs (BERT, GPT, Llama, etc.).
• Build data ingestion and preprocessing pipelines using Python, Pandas, and FastAPI.
• Integrate LLMs and AI agents using frameworks such as LangChain, LlamaIndex, or OpenAI API.
• Implement MLOps workflows — including model tracking, CI/CD, and monitoring with tools like MLflow or DVC.
• Deploy and scale models using Docker, Kubernetes, AWS/GCP/Azure, or serverless architectures.
• Collaborate with cross-functional teams (data, frontend, product) to build and ship AI-driven features.

Required Skills

Programming:

• Backend: Node.js (Express/Nest.js), FastAPI
• ML/AI: Python, TensorFlow, PyTorch, scikit-learn

AI/ML Tools:

• Hugging Face Transformers, LangChain, OpenAI API, LlamaIndex

Data Handling:

• Pandas, NumPy, SQL/NoSQL databases

DevOps/MLOps:

• Docker, Kubernetes, Git, MLflow, DVC

API Development:

• REST, GraphQL, WebSocket

Cloud Deployment:

• AWS (SageMaker/Lambda), GCP (Vertex AI), Azure ML

Additional Expertise:

• Strong understanding of LLM architecture, embeddings, and vector databases such as Pinecone, FAISS, or Milvus.

Good to Have

• Experience with TypeScript for Node.js backend.
• Worked on chatbots, RAG (Retrieval-Augmented Generation) systems, or AI assistants.
• Familiarity with FastAPI async endpoints for real-time inference.
• Exposure to model quantization and optimization for faster inference.
• Experience integrating FastAPI microservices into Node.js ecosystems.

Education

B.Tech / M.Tech / MCA in Computer Science, Artificial Intelligence, or a related field.

Job Type: Full-time

Application Question(s):

• Are you familiar with RAG, Generative AI, and Computer Vision ?
• Have you worked on Deploying ML models into Production?

Experience:

• AI: 3 years (Required)

Work Location: In person