Data Scientist

Kanini Software Solutions; Pune District, Chennai, Bengaluru; Hybrid; INR 150.000 - 250.000; Vollzeit

Zusammenfassung

Kanini Software Solutions in Pune invites a skilled Data Scientist to own end-to-end GenAI/ML initiatives on GCP, building production-grade Python services with FastAPI.

You will deploy on Cloud Run, design scalable APIs, and implement CI/CD, collaborating with Product, Data Eng, and Infra teams to modernize ML platforms.

Candidates should be proficient in OOP, embeddings, and API management to deliver robust, scalable ML solutions.

Qualifikationen

• Strong hands-on Python and GenAI/LLM development experience.
• GCP ML pipelines and deployment services experience.
• Proficient in FastAPI, API development, and CI/CD workflows.

Aufgaben

• Build, train, and optimize ML/GenAI models (RAG, embeddings, LLM integrations).
• Develop production-grade services using Python + FastAPI.
• Deploy ML workloads on GCP (Cloud Run, BigQuery, GCS, Pub/Sub).
• Design scalable APIs and lead API integrations.
• Contribute to Cloud Migration and ML platform modernization.
• Implement CI/CD for ML pipelines and microservices.
• Apply OOPS principles for clean, modular design.
• Work collaboratively with Product, Data Engineering, and Infra teams.

Kenntnisse

Python

GenAI/LLM

GCP ML pipelines

FastAPI

CI/CD

API Development

OOP fundamentals

Tools

Docker

Kubernetes

Pinecone

FAISS

Chroma

Terraform

IaC

Jobbeschreibung

About the Role

Were looking for a strong Data Scientist with hands-on development capability (Python, FastAPI, OOPs),

solid GenAI/LLM experience, and the ability to work end-to-end on GCP-based ML solutions including

deployment, APIs, and CI/CD.

Key Responsibilities

• Build, train, and optimize ML/GenAI models (RAG, embeddings, LLM integrations)
• Develop production-grade services using Python + FastAPI
• Deploy ML workloads on GCP (Cloud Run, BigQuery, GCS, Pub/Sub)
• Design scalable APIs and lead API integrations
• Contribute to Cloud Migration and ML platform modernization
• Implement CI/CD for ML pipelines and microservices
• Apply OOPS principles for clean, modular design
• Work collaboratively with Product, Data Engineering, and Infra teams

Must-Have Skills

• Strong hands-on Python
• GenAI / LLM development
• GCP ML pipelines and deployment services
• FastAPI
• CI/CD (Jenkins / GitHub Actions)
• API Development & API Management
• Solid OOPS fundamentals

Nice-to-Have

• Docker / Kubernetes
• Vector DBs (Pinecone / FAISS / Chroma)
• Terraform / IaC