Data Scientist

Position Overview

Data Scientist

Key Responsibilities

1. Machine Learning & Generative AI

• Develop, train, and optimize

  machine learning

  ,

  deep learning

  , and

  generative AI

  models (LLMs, diffusion models, transformers, etc.).
• Build GenAI-driven applications such as chatbots, summarization tools, embeddings-based search, and automated decisioning systems.
• Implement and fine-tune LLMs using

  Vertex AI

  tools like Vertex AI Training, Vertex AI Pipelines, Vector Search, and Model Garden.

2. Data Engineering & Pipelines

• Build scalable data pipelines and feature stores using Python, Java, and cloud services.
• Work with structured and unstructured data (text, image, audio, logs).
• Ensure data quality, preprocessing, and robust data transformations for ML readiness.

3. Deployment & MLOps

• Deploy and monitor ML/GenAI models in production using

  Vertex AI

  , Vertex Endpoints, and CI/CD pipelines.
• Implement model versioning, A/B testing, and performance monitoring.
• Collaborate with MLOps engineers to scale models across environments.

4. Cross-functional Collaboration

• Work closely with product managers, engineers, and business stakeholders to translate requirements into technical solutions.
• Communicate findings, insights, and recommendations to both technical and non-technical audiences.

Required Skills & Qualifications

Technical Must-Haves

• Strong coding skills in Java and Python

• (ability to develop production-grade services and ML codebases)

• Hands-on experience with Generative AI

• (LLMs, prompt engineering, fine-tuning, embeddings, RAG pipelines)

• Expertise with Google Cloud Vertex AI