Data Scientist

Job Description

Job Description (JD): Principal Applied Data Scientist – OCI Generative AI Solutions
Company

Oracle

Business Unit

Oracle Cloud Infrastructure (OCI) – Generative AI Service

Job Title

Principal Applied Data Scientist

Career Level

IC4 (Individual Contributor)

Job Summary

Oracle Cloud Infrastructure (OCI) is seeking an experienced Principal Applied Data Scientist to join its OCI Generative AI Solutions Team. The role focuses on designing, developing, and deploying enterprise-scale Generative AI solutions for Oracle’s strategic customers using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Model Predictive Control (MPC), OpenSearch, and Vector Databases.

The successful candidate will work directly with enterprise customers across industries such as financial services, healthcare, telecommunications, and software engineering to architect scalable AI solutions on Oracle Cloud Infrastructure.

Key Responsibilities
Customer Solution Architecture
Partner directly with strategic customers to understand business requirements.
Design end-to-end Generative AI architectures.
Guide customers throughout their AI adoption journey.
Collaborate with customer ML Engineering teams to resolve technical challenges.
Generative AI Development
Design and implement enterprise-grade Generative AI solutions.
Develop scalable LLM-powered applications.
Build reusable AI solution templates and reference architectures.
Optimize model performance and scalability.
Retrieval-Augmented Generation (RAG)
Design and implement RAG architectures.
Integrate enterprise knowledge bases with LLMs.
Build scalable retrieval pipelines.
Optimize retrieval quality and response accuracy.
OpenSearch Engineering
Configure and manage large-scale OpenSearch clusters.
Build data ingestion pipelines.
Optimize search performance.
Improve indexing strategies.
Reduce query latency.
AI Engineering
Develop production-ready AI systems.
Troubleshoot AI model training and inference issues.
Optimize deployment pipelines.
Improve scalability and availability.
AI Evangelism
Present Oracle AI capabilities to customers.
Participate in technical conferences.
Demonstrate OCI Generative AI solutions.
Promote AI best practices.
Leadership
Mentor junior ML Engineers.
Guide Applied Scientists.
Share best practices across engineering teams.
Required Technical Skills
Programming Languages
Python
Shell Scripting
Generative AI

Strong experience with:

Large Language Models (LLMs)
Generative AI
AI Agents
Model Predictive Control (MPC)
Prompt Engineering
Tree-of-Thoughts
Instruction Fine-tuning
Parameter Efficient Fine-Tuning (PEFT)
LLM Frameworks

Experience with:

LangChain
LlamaIndex
LMQL
Guidance
MLflow (LLMOps)
Retrieval-Augmented Generation
RAG Architecture
Vector Retrieval
Knowledge Retrieval
Semantic Search
Search Technologies
OpenSearch
Search Optimization
Indexing
Search Algorithms
Low-Latency Search
Conversational Search
Multimodal Search
Databases
PostgreSQL
Vector Databases
Streaming
Kafka
Kafka Streaming
Machine Learning

Strong understanding of:

Machine Learning
Deep Learning
Transformer Architecture
Optimizers
Neural Network Training
AI Model Deployment
Deep Learning Frameworks

Experience with:

PyTorch
TensorFlow
JAX
ML Infrastructure

Knowledge of:

Kubeflow
KServe
Triton Inference Server
Cloud Computing

Experience with:

Oracle Cloud Infrastructure (OCI)
Public Cloud Platforms
IaaS
PaaS
Required Experience
Bachelor’s or Master’s degree in Computer Science or related technical discipline.
10+ years of professional experience in AI, Machine Learning, Data Science, or ML Engineering.
Experience designing production-grade AI solutions.
Experience collaborating with Product Managers and Engineering teams.
Experience leading enterprise AI implementations.
Preferred Qualifications

Candidates with experience in the following areas will have an advantage:

Retrieval-Augmented Generation (RAG)
Vector Search
Semantic Search
Conversational AI
Multimodal AI
Computer Vision
Agentic AI
OpenSearch Optimization
Large-scale AI Infrastructure
LLM Fine-tuning
Model Serving
AI Production Systems
Research Experience

Preferred candidates should have:

Publications in top-tier conferences or journals.
Experience serving as reviewer or lead author.
Strong research background in AI/ML.
Soft Skills
Excellent communication skills
Customer-facing consulting experience
Technical leadership
Solution architecture
Mentoring and coaching
Problem-solving
Collaboration
Innovation mindset
Presentation skills
Industries Supported

Solutions will primarily target:

Financial Services
Healthcare
Telecommunications
Software Engineering
Enterprise AI
Tools & Technologies
Programming
Python
Shell
AI Frameworks
LangChain
LlamaIndex
MLflow
LMQL
Guidance
Deep Learning
PyTorch
TensorFlow
JAX
Search
OpenSearch
Vector Search
Semantic Search
Databases
PostgreSQL
Vector Databases
Streaming
Kafka
Infrastructure
Kubeflow
KServe
Triton
AI Techniques
LLMs
RAG
AI Agents
PEFT
Prompt Engineering
Tree-of-Thoughts
Instruction Fine-Tuning