Lead Scientist, Data Science

XPO Logistics, Inc.; Pune District; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

XPO Logistics, Inc. is seeking a Lead Data Scientist in Pune to design and productionize advanced AI/ML solutions, including Generative AI and RAG-based architectures.

You will own end-to-end model lifecycles, collaborate with engineering, and mentor data science teams to drive measurable business impact. Applicants should have deep MLOps experience, model governance, and strong leadership to scale AI across products and operations.

Qualifications

• Experience with Generative AI and RAG architectures.
• Preferred background in end-to-end ML lifecycle and production-grade ML systems.
• Strong MLOps, model governance, and scalable deployment experience.

Responsibilities

• Design, build, and productionize AI/ML solutions including Generative AI and RAG.
• Lead end-to-end model lifecycle: data prep, feature engineering, training, evaluation, deployment, monitoring.

Skills

Generative AI

RAG pipelines

MLOps

ML engineering

LLMs

Diffusion models

Transformers

Vector DBs

Pinecone

Weaviate

FAISS

Retrieval systems

Tools

MLflow

Kubeflow

Airflow

Job description

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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.