Lead Scientist, Data Science

XPO; Maharashtra; On-site; INR 1,800,000 - 3,200,000; Full time

Benefits offered by this job

Job summary

XPO in Maharashtra seeks a Lead Data Scientist to architect Generative AI and RAG solutions, productionizing models with strong MLOps. You will lead data science teams and collaborate with product and engineering to deliver reliable AI systems.

Responsibilities include end-to-end model lifecycle, governance, and continuous innovation; you will mentor engineers and translate AI value to business outcomes.

Qualifications

• Proven experience building Generative AI and RAG-based systems.
• Strong background in MLOps, CI/CD for ML and model monitoring.
• Experience productionizing ML/AI solutions at scale.

Responsibilities

• Design, build, and productionize advanced ML/AI models (Generative AI, RAG).
• Lead end-to-end model lifecycle: data prep, training, deployment, monitoring.
• Establish and optimize MLOps pipelines for CI/CD and monitoring.
• Enforce governance, reproducibility, and scalability of models.
• Collaborate with engineering to integrate AI into production systems.
• Provide technical leadership and mentorship to data scientists and ML engineers.
• Partner with product and business to translate AI concepts into value.
• Evaluate emerging AI technologies to drive innovation.

Skills

Generative AI

RAG pipelines

MLOps

Productionizing ML models

ML Engineering

Technical leadership

Mentorship

Stakeholder communication

Tools

MLflow

Kubeflow

Airflow

Pinecone

Weaviate

FAISS

Job description

We are seeking a highly skilled Lead Data Scientist with deep expertise in Generative AI, Retrieval-Augmented Generation (RAG), and productionizing advanced machine learning models. The ideal candidate will have strong experience in MLOps and ML Engineering, ensuring scalable, reliability, and secure deployment of AI solutions into production environments. This role requires both technical leadership and strategic vision to drive impactful AI initiatives across the organization.

Key Responsibilities

• AI Solution Development


• Design, build, and productionize advanced ML/AI models, including Generative AI and RAG-based architectures.


• Lead end-to-end model lifecycle: data preparation, feature engineering, training, evaluation, deployment, and monitoring.


• Establish and optimize MLOps pipelines for continuous integration, deployment, and monitoring of ML models.


• Implement best practices for model governance, reproducibility, and scalability.


• Collaborate with engineering teams to ensure seamless integration of AI solutions into production systems.


• Provide technical leadership and mentorship to data scientists and ML engineers.


• Partner with product and business stakeholders to translate complex AI concepts into actionable business value.


• Drive innovation by evaluating emerging AI technologies and frameworks.


• Operational Excellence


• Ensure AI models meet performance, reliability, and compliance standards.


• Develop monitoring frameworks for model drift, bias detection, and performance degradation.


• Champion responsible for AI practices and security-first approaches.

Required Skills & Experience

• Technical Expertise


• Proven experience in Generative AI (LLMs, diffusion models, transformers) and RAG pipelines.


• Strong background in MLOps (CI/CD for ML, model monitoring, orchestration tools like MLflow, Kubeflow, Airflow).


• Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval systems.