Hiring Data Scientist – Gen AI Development

ob Title: Data Scientist – GenAI & Cloud (Java/Python + Vertex AI)
Experience: 6–9 Years
Location: Remote (Base Location: Pune, Indore, Ahmedabad, Hyderabad, Bangalore)
Contract Duration: 6 Months

About the Role

We are looking for a highly skilled Data Scientist experienced in GenAI, ML model development, hands-on coding (Java & Python) and cloud-based deployment using Google Vertex AI. The ideal candidate should have strong capabilities in building scalable ML pipelines, training/evaluating models, and integrating ML solutions into production systems.

Key ResponsibilitiesAI/ML & GenAI

• Develop ML and GenAI solutions including LLM, NLP, embeddings, and retrieval workflows.
• Build end-to-end ML pipelines — data ingestion, training, validation, deployment, and monitoring.
• Fine-tune or optimize LLM-based applications on Vertex AI.
• Build RAG workflows, model evaluation experiments, and benchmarking frameworks.

Hands-on Coding

• Strong coding in Python for model development and data engineering tasks.
• Ability to write Java code for integrating ML models into microservices or backend systems.
• Develop APIs, services, and tools for model inference & automation.

Vertex AI & Cloud Deployment

• Use Vertex AI (Training, Endpoint, Pipelines, Model Registry) for scalable model development.
• Deploy serverless ML services using Cloud Run, Cloud Functions, or other GCP components.
• Optimize ML workloads for speed, cost, and scalability.

Required Skills

• Strong programming in Python and good coding skills in Java.
• Hands-on experience with GenAI, LLMs, NLP pipelines.
• Expertise in Vertex AI (training, endpoints, pipelines).
• Strong knowledge of ML algorithms & deep learning frameworks (TensorFlow, PyTorch).
• Experience with cloud-native development (GCP preferred).
• Working knowledge of APIs, microservices, and serverless deployments (Cloud Run).

Data Science & Analytics

• Perform data preprocessing, feature engineering, data modeling, and exploratory analysis.
• Work with structured and unstructured datasets (text, logs, documents, vector data).
• Conduct experiments, A/B tests, hyperparameter tuning, and model monitoring.

Collaboration & Best Practices

• Work closely with engineering and architecture teams.
• Follow MLOps, DevOps, CI/CD, versioning, and production readiness guidelines.
• Maintain clean code, documentation, and reproducibility practices.

Job Type: Contractual / Temporary

Pay: ₹1,500,000.00 - ₹1,600,000.00 per year

Work Location: Remote