FedEx - Data Scientist - GenAI

Job Description :

Job Title : Decision Scientist

Role Overview :

We are seeking a Senior Decision Scientist with 6-8 years of experience to design and build enterprise-grade Generative AI solutions. The role focuses on developing and deploying LLM-based applications, including RAG architectures, fine-tuning strategies, and context management using MCP. The candidate will work with secure, scalable enterprise LLM platforms, collaborate with cross-functional teams, and deliver production-ready AI systems. Experience in predictive or forecasting ML models is a strong added advantage.

What your main responsibilities are :

- Design, develop, and deploy LLM-powered applications for enterprise use cases

Build and optimize RAG pipelines, including :

i. Vector databases and embeddings

ii. Document ingestion, chunking, indexing, and retrieval strategies

iii. Implement and evaluate fine-tuning approaches (SFT, LoRA, adapters, PEFT techniques)

- Work with enterprise LLM platforms ensuring :

Data security, privacy, and compliance

Token efficiency, latency optimization, and cost control

Integrate MCP (Model Context Protocol) or equivalent approaches to manage model context, tool usage, and structured prompts

Develop robust prompt engineering and prompt orchestration strategies

Design scalable APIs and microservices to serve GenAI workloads

Evaluate open-source and commercial LLMs (OpenAI, Azure OpenAI, Anthropic, open source models, etc.)

- Collaborate with MLOps and Platform teams on :

Model monitoring and observability

Versioning, rollback, and lifecycle management

Partner with business and product stakeholders to translate requirements into production ready GenAI solutions

What we are looking for :

Required Qualifications :

- 6 to 8 years of overall software / data / ML experience

Strong hands-on experience with LLMs and GenAI frameworks

- Proven experience building RAG-based systems in production

Solid understanding of LLM fine-tuning techniques

- Experience working with enterprise LLM deployments (private endpoints, governance, security controls)

- Strong proficiency in Python

Experience with libraries such as LangChain, LlamaIndex, Transformers, or similar

- Familiarity with vector databases (e.g., FAISS, Pinecone, Milvus, Weaviate, Azure AI Search)

- Good understanding of REST APIs, microservices, and cloud-native architectures

Enterprise & Platform Understanding

- Experience handling enterprise data (structured & unstructured)

Understanding of data privacy, compliance, and responsible AI practices

- Experience deploying models on cloud platforms (Azure, AWS, or GCP)

Good to Have / Added Advantage :

- Experience with ML predictive modeling or time-series forecasting

Exposure to traditional ML workflows (feature engineering, model evaluation, deployment)

- Experience with MLOps tools and pipelines

Familiarity with search relevance, ranking models, or recommendation systems

- Experience mentoring junior engineers or leading technical initiatives

What you can expect to get :

An attractive and comprehensive compensation and benefits package including :

- Competitive salary and performance-based rewards

- Tuition assistance and 24/7 access to professional learning platforms

- Career advancement opportunities through internal mobility, job rotations, and leadership development programs

- Hybrid work model supporting work-life balance (mix of office and remote work)

- Health & wellness, employee assistance, and recognition programs

- Exclusive employee discounts on FedEx services, travel, and partner offerings