Junior Backend Engineer – AI/ML Platform

Kaala Ghoda; Thane; On-site; INR 800,000 - 1,400,000; Full time

Job summary

Kaala Ghoda in Mumbai is seeking a hands-on Junior Backend Engineer with 2 years of backend/data engineering experience to join an early-stage startup building a predictive marketing engine. You will own data pipelines, containerise models, and develop APIs to serve inferences.

The role offers an on-site, 6-month contract with a clear path to full-time conversion, exposure to MLOps, PyTorch, and fast-paced delivery in a startup environment where speed matters.

Qualifications

• 2 years of professional software engineering experience, backend or data engineering.
• Strong Python and FastAPI/Flask experience.
• Hands-on Docker containerization experience.
• Experience with PostgreSQL and MongoDB.
• Familiarity with PyTorch, Hugging Face pipelines, or LLM APIs.

Responsibilities

• Data Pipeline Ownership: Maintain and optimise ETL pipelines from live endpoints to staging databases.
• ML Deployment (MLOps): Help containerise PyTorch models and deploy under guidance.
• Code Quality: Refactor MVP research code into production-ready Python.
• API Development: Build and optimise backend endpoints to serve ML inferences.
• CI/CD & Monitoring: Manage Git workflows and monitor model performance and API latency.

Skills

Python

API development

SQL

NoSQL

ML/AI familiarity

Docker

Tools

Docker

FastAPI/Flask

PostgreSQL

MongoDB

PyTorch

Hugging Face

Job description

Type: 6-Month Contract (With a clear pathway to Full-Time conversion)

Location: Mumbai (On-site)

About Us

We are an early-stage startup building a next-generation Predictive Marketing Engine. We are moving the ad industry away from human guesswork and into mathematical certainty.

The Role

We are looking for a hands-on, execution-focused Junior Backend Engineer with 2 years of relevant experience and a strong working knowledge of AI and ML ecosystems. You will be working to ensure our automated data pipelines never break, models are containerised correctly, and backend APIs are managed. If you are a backend engineer looking to transition deeply into MLOps, or an ML engineer who prides themselves on clean code and system stability, this role is for you.

Key Responsibilities

• Data Pipeline Ownership: Maintain and optimise robust ETL pipelines pulling live data from endpoints into our staging databases.
• ML Deployment (MLOps Support): Assist in containerising our existing PyTorch models, transformers, and LLM scripts using Docker, and deploying them under the guidance.
• Code Quality: Refactor existing MVP research code into clean, modular, production-ready Python following team standards.
• API Development: Write and optimise backend endpoints using FastAPI/Flask to seamlessly serve ML model inferences to our frontend client.
• CI/CD & Monitoring: Manage Git workflows, maintain environment consistency, and monitor live model performance, API latencies, and logs.

What You Bring (Requirements)

• Experience: 2 years of professional software engineering experience, focused on backend development or data engineering.
• Core Stack: Strong proficiency in Python and web framework development (FastAPI/Flask preferred).
• Containerization: Practical, hands-on experience writing Dockerfiles and managing containerised applications.
• Databases: Solid understanding of SQL (PostgreSQL) and NoSQL (MongoDB) for managing unstructured text data and user state.
• AI/ML Familiarity: Basic experience interacting with PyTorch, Hugging Face pipelines, or commercial LLM APIs (OpenAI/Gemini). You should understand how to pass data through an API to a model.

Bonus Points (Nice-to-Haves)

• Experience with frontend frameworks (React/Next.js) or building quick internal tools using Streamlit.
• Basic knowledge of Agentic AI or Multi-Agent workflows (LangChain, LlamaIndex, AutoGen).
• Familiarity with AdTech APIs (Google Ads, Meta Ads).

What You Get

Direct mentorship and hands-on exposure to PyTorch, LLMs, MLOps, and cloud infrastructure.

Clear path to a full-time role.

A startup environment where your work ships fast and matters immediately.