Data Scientist

Rocket Learning; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Rocket Learning is seeking a Data Scientist to design, build, and deploy ML and LLM-based systems that empower personalized learning, support teachers, and improve programs in Bengaluru with remote/hybrid options.

You will develop, evaluate, and deploy ML models, build reproducible pipelines, collaborate with product and domain teams, and continuously improve performance and reliability.

Qualifications

• 3-6 years in applied ML / ML engineering / NLP / LLM development.
• Strong fundamentals: statistics, ML algorithms, deep learning.
• Experience with LLMs, fine-tuning, embeddings, vector stores, RAG.
• Experience deploying models via APIs or containerized workflows.

Responsibilities

• Develop, evaluate, and deploy ML, deep learning & LLM models.
• Build reproducible, well-documented model workflows & pipelines.
• Collaborate with product & domain teams to shape modeling strategies.
• Continuously improve performance, documentation, reliability & processes.

Skills

Applied ML

NLP

Deep learning

LLM development

Experiment tracking

Tools

MLflow

Experiment tracking

Model registries

Job description

Data Scientist

(3-6 years of experience - Remote/Hybrid Bengaluru)

Design, build, and deploy ML and LLM-based systems that drive personalization, assist teachers, and improve programs.

What you’ll do

• Develop, evaluate, and deploy ML, deep learning & LLM models


• Build reproducible, well-documented model workflows & pipelines


• Collaborate with product & domain teams to shape modeling strategies


• Continuously improve performance, documentation, reliability & processes

What we’re looking for

• 3-6 years in applied ML / ML engineering / NLP / LLM development


• Strong fundamentals: statistics, ML algorithms, deep learning


• ML workflow tools (MLflow, experiment tracking, registries)


• Experience with LLMs, fine-tuning, embeddings, vector stores, RAG


• Experience deploying models through APIs or containerized workflows

Key Success Factors

• Excellent communication and collaboration across teams to translate needs into solutions


• Curiosity, fundamentals, and bias for shipping reliable systems