Junior Backend Engineer – AI/ML Platform

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

How to Apply

If you thrive in fast-paced startup environments and want to build a deep-tech architecture from the ground up, send your resume, salary expectations, references and GitHub/LinkedIn/portfolio/personal website to:

sampark@kaalaghoda.com