We’re looking for a strong Data Scientist with hands-on development capability (Python, FastAPI, OOPs), solid GenAI and LLM experience, and the ability to work end-to-end on GCP/Azure/AWS based ML solutions including deployment, APIs, and CI/CD.

Key Responsibilities

Build, train, and optimize ML and GenAI models (RAG, embedding, LLM integrations)
Develop production-grade services using Python + FastAPI
Deploy ML workloads on GCP/Azure/AWS
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

Requirements

Strong hands-on Python
GenAI / LLM development
FastAPI
CI/CD (Jenkins / GitHub Actions)
API Development & API Management
Solid OOPS fundamentals
GCP/Azure/AWS

Nice-to-Have

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

Erforderliche Kompetenzen

Python (hands-on development)GenAI / LLM developmentRetrieval-Augmented Generation (RAG) & embedding techniquesML model training and optimizationFastAPI (production-grade service development)Object-Oriented Programming (OOPS) principlesCloud ML deployment (GCP / Azure / AWS)CI/CD for ML pipelines and microservices (Jenkins / GitHub Actions)API design, development and API managementCloud migration and ML platform modernizationCross-functional collaboration with Product, Data Engineering, and Infra teamsDocker and Kubernetes (containerization & orchestration)Vector databases (Pinecone / FAISS / Chroma)Terraform / Infrastructure-as-Code (IaC)

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