Data Scientist

About the Role

Data Scientist / GenAI Engineer

You’ll work on designing and developing AI-powered applications, optimizing data pipelines, and fine-tuning large models for real-world business use cases.

Key Responsibilities

• Design and implement

  end-to-end GenAI and RAG solutions

  using LLM frameworks and vector databases.
• Develop, fine-tune, and evaluate

  Large Language Models (LLMs)

  for NLP tasks such as summarization, Q&A, and contextual reasoning.
• Collaborate with data engineers and business stakeholders to translate business needs into scalable AI solution
• Work on

  Machine Learning model development

  — from data preprocessing to model evaluation and deployment.
• Utilize

  Databricks

  for data wrangling, experimentation, and model lifecycle management.
• Integrate GenAI models with existing data ecosystems through APIs and custom pipelines.
• Optimize performance, latency, and cost for AI/ML workloads in production environments.
• Research emerging trends in

  Agentic AI

  ,

  LLMs

  , and

  RAG pipelines

  , bringing innovative ideas into product development.

Required Skills & Experience

• 3+ years of experience in

  Machine Learning

  ,

  Natural Language Processing

  , or

  Generative AI

  .
• Hands-on experience with

  LLMs (GPT, Llama, Claude, Gemini, etc.)

  and

  RAG architecture

• Proficiency in

  Python

  ,

  PyTorch

  , or

  TensorFlow

  .
• Experience with

  Databricks

  for ML workflow orchestration and large-scale data processing.
• Familiarity with

  Vector Databases (Pinecone, FAISS, Weaviate, ChromaDB)

  .
• Understanding of

  prompt engineering

  ,

  fine-tuning

  , and

  embedding generation

  .
• Experience in

  end-to-end ML lifecycle

  — data collection, preprocessing, model building, and deployment.
• Strong understanding of

  SQL

  and

  data engineering concepts

  .

Good to Have

• Knowledge of

  LangChain

  ,

  LlamaIndex

  , or similar frameworks for agentic AI workflows.
• Experience deploying GenAI models on

  Azure OpenAI

  ,

  AWS Bedrock

  , or

  GCP Vertex AI

  .
• Familiarity with

  MLOps practices

  (CI/CD, model monitoring, versioning).
• Exposure to

  Databricks Unity Catalog

  and

  Delta Live Tables (DLT)

  .

Key Attributes

• Excellent analytical and problem-solving abilities.
• Strong communication and collaboration skill
• Passion for continuous learning and innovation in AI.
• Ability to translate business challenges into AI-driven solutions.