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Oracle · 2 months ago

Principal Cloud Architect, AI Computational Data Scientist

United States

Full-time

Remote

Senior Level, Lead/Staff

$113K/yr - $185K/yr

6+ years exp

Oracle Cloud Infrastructure (OCI) is a pioneering force in cloud technology, merging the agility of startups with the robustness of an enterprise software leader. In this role, you'll collaborate with applied scientists and product managers to design, develop, and deploy tailored Gen-AI solutions with an emphasis on Large Language Models, aimed at addressing complex global challenges.

Data GovernanceData ManagementEnterprise SoftwareInformation TechnologySaaSSoftware

No H1B

Responsibilities

Work directly with key customers and accompany them on their Gen AI journey – understanding their requirements, help them envision and design and build the right solutions and work together with their ML engineering to remove blockers

You will dive deep into model structure to optimize model performance and scalability

You will build state of art solutions with brand new technologies in this fast-evolving area

You will configure large scale OpenSearch clusters, setting up ingestion pipelines to get the data into the OpenSearch

You will diagnose, troubleshoot, and resolve issues in AI model training and serving. You may also perform other duties as assigned

Build re-usable solution patterns and reference solutions / showcases that can apply across multiple customers

Be an enthusiastic, self-motivated, and a great collaborator

Be our product evangelist - engage directly with customers and partners, participate and present in external events and conferences, etc

Qualification

Large Language ModelsOpenSearchAI solutions architectureMachine LearningPythonData ingestion pipelinesVector databasesKafka StreamingTechnical communicationMentoringCollaboration

Required

Doctoral or master's degree in computer science or equivalent technical field with 10+ years of experience

Able to optimally communicate technical ideas verbally and in writing (technical proposals, design specs, architecture diagrams and presentations)

Demonstrated experience in designing and implementing scalable AI models and solutions for production, relevant professional experience as end-to-end solutions engineer or architect (data engineering, data science and ML engineering is a plus), with evidence of close collaborations with PM and Dev teams

Experience with OpenSearch, Vector databases, PostgreSQL and Kafka Streaming

Practical experience with setting up and finetuning large OpenSearch Clusters

Experience in setting up data ingestion pipelines with OpenSearch

Experience with search algorithms, indexing, optimizing latency and response times

Practical experience with the latest technologies in LLM and generative AI, such as parameter-efficient fine-tuning, instruction fine-tuning, and advanced prompt engineering techniques like Tree-of-Thoughts

Familiarity with Agents and Agent frameworks and Model Context Protocol (MCP)

Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc

Strong publication record, including as a lead author or reviewer, in top-tier journals or conferences

Ability and passion to mentor and develop junior machine learning engineers

Proficient in Python and shell scripting tools

Preferred

PhD/Masters in related field with 5+ years relevant experience

Experience with RAG based solutions architecture. Familiarity in OpenSearch and Vector stores as a knowledge store

Knowledge of LLM and experience delivering, Generative AI And Agent models are a significant plus

Familiarity and experience with the latest advancements in computer vision and multimodal modeling is a plus

Experience with semantic search, multi-modal search and conversational search

Experience in working on a public cloud environment, and in-depth knowledge of IaaS/PaaS industry and competitive capabilities. Experience with popular model training and serving frameworks like KServe, KubeFlow, Triton etc

Experience with LLM fine-tuning, especially the latest parameter efficient fine-tuning technologies and multi-task serving technologies

Deep technical understanding of Machine Learning, Deep Learning architectures like Transformers, training methods, and optimizers

Experience with deep learning frameworks (such as PyTorch, JAX, or TensorFlow) and deep learning architectures (especially Transformers)

Experience in diagnosing, fixing, and resolving issues in AI model training and serving

Benefits

Medical, dental, and vision insurance, including expert medical opinion

Short term disability and long term disability

Life insurance and AD&D

Supplemental life insurance (Employee/Spouse/Child)

Health care and dependent care Flexible Spending Accounts

Pre-tax commuter and parking benefits

401(k) Savings and Investment Plan with company match

Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation.

11 paid holidays

Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours.

Paid parental leave

Adoption assistance

Employee Stock Purchase Plan

Financial planning and group legal

Voluntary benefits including auto, homeowner and pet insurance