FDE AI

MathCo; Bengaluru; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

MathCo in Bengaluru is seeking a senior data scientist to build GenAI applications, including RAG, agents, and Text2SQL, and to deploy LLMs at scale.

You will collaborate with customers across industries, optimize ML workloads with MLOps, mentor the ML team, and contribute to product roadmaps with cross-functional partners.

Qualifications

• 5+ years of data science / ML experience.
• Experience with pandas, MLflow, scikit-learn, PyTorch.
• Experience building production-grade GenAI deployments on AWS/Azure/GCP.

Responsibilities

• Develop LLM solutions on customer data (RAG architectures).
• Assist customers across Health, Finance, Retail, Startups, etc.
• Scale and optimize customer data science workloads with MLOps.
• Advise data teams on architecture and tooling.
• Provide thought leadership by presenting at Data+AI Summit and mentoring ML team.
• Collaborate with product and engineering to shape roadmap.

Skills

Generative AI

RAG

Agents

Text2SQL

Fine-tuning

LLM deployment

HuggingFace

LangChain

OpenAI

Pandas

MLflow

Scikit-Learn

PyTorch

AWS

Azure

GCP

Communication

Mentoring

Databricks

Apache Spark

Tools

HuggingFace

LangChain

OpenAI

Databricks

Apache Spark

AWS

Azure

GCP

Job description

• Experience in building Generative AI applications, including RAG, agents, Text2SQL, fine-tuning, and deploying LLMs, using tools such as HuggingFace, Langchain, and OpenAI
• 5+ years of hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, MLflow, scikit-learn, and PyTorch
• Experience in building production-grade ML or GenAI deployments on AWS, Azure, or GCP.
• Experience in communicating and teaching technical concepts to both non-technical and technical audiences
• Passion for collaboration, life-long learning, and driving business value through ML
• Preferred - Experience working with Databricks and Apache Spark

The impact you will have:

• Develop LLM solutions on customer data, such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation
• Help customers solve tough problems across industries like Health and Life Sciences, Finance, Retail, Startups, and many others
• Build, scale, and optimize customer data science workloads across industries and apply best-in-class MLOps to productionize these workloads
• Advise data teams on data science architecture, tooling, and best practices
• Provide thought leadership by presenting at conferences such as Data+AI Summit and mentoring the larger ML Team
• Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap