Junior ML Engineer

Role Overview

As a Junior ML Engineer, you’ll be exposed to real-world machine learning systems from day one. You’ll support model development, testing, and deployment — and also take ownership of core data tasks like ingestion, vectorization, and indexing that form the backbone of our AI search engine.

This role is perfect for someone who wants to grow fast, work with state-of-the-art AI tools, and help shape the future of legal research.

Key Responsibilities

1. Assist in Building and Deploying AI Models

Support senior ML engineers in developing search relevance models using LLMs and RAG.
Help test and evaluate embedding quality, ranking performance, and retrieval accuracy.
Contribute to deploying models into production on Azure.

2. Learn and Grow in a Production AI Environment

Gain exposure to real-world ML workflows used in legal and enterprise search.
Receive mentorship on best practices in model design, deployment, and optimization.
Participate in code reviews, architecture discussions, and technical deep dives.

3. Build APIs and Contribute to Integration Work

Help create and maintain REST APIs that expose AI-powered search to frontend apps.
Work alongside full-stack engineers to ensure seamless integration of models.

4. Manage Data Pipelines for Legal Search

Ingest, preprocess, and structure legal documents for AI consumption.
Chunk and generate embeddings from legal texts using pre-trained models.
Continuously update Azure AI Search indexes by ingesting fresh legal data on a regular basis.

Required Skills & Experience

2–3 years of experience or strong academic projects in ML/NLP/data science.
Strong programming skills in Python and experience with PyTorch or TensorFlow.
Familiarity with LLMs, vector search including Azure AI Search and RAG workflows.
Exposure to FastAPI, Flask, or Azure ML services.
Experience with data processing libraries (Pandas, NumPy, spaCy, NLTK).
On-site position for Lucknow, India.

Nice to Have

Experience working with legal, academic, or enterprise document data.
Interest in AI-powered document search or legal/enterprise NLP applications.
Strong desire to learn and collaborate with senior ML engineers.