Note: The job is a remote job and is open to candidates in USA. Oracle is a company providing cloud, infrastructure, applications, data, and AI solutions. The Principal Data Scientist will develop, evaluate, and productionize applied AI and machine-learning capabilities for enterprise customer and platform use cases, collaborating with engineering, product, customer, and scientific teams. The role focuses on experimentation, model evaluation, prototyping, production deployment, and continuous improvement across generative AI, RAG, agentic systems, and cloud AI services.
Responsibilities
- Develop, evaluate, and improve applied AI and machine-learning solutions for customer and platform use cases
- Work with product and customer teams to understand domain workflows, user needs, data characteristics, and success criteria
- Design and execute experiments to assess model quality, reliability, latency, cost, safety, and customer value
- Build prototypes and proof-of-concepts that validate technical approaches and inform product decisions
- Develop model-evaluation frameworks, test sets, benchmarks, and measurement approaches for AI capabilities
- Contribute to RAG, agentic AI, model-training, model-serving, or Model Context Protocol (MCP) based solutions
- Partner with software engineers to productionize models, prompts, pipelines, evaluation harnesses, and AI-service integrations
- Analyze model behavior, customer feedback, and product telemetry to identify quality gaps and recommend improvements
- Help define data requirements, data-preparation approaches, and responsible-AI considerations for supported use cases
- Contribute to technical documentation, design reviews, knowledge sharing, and scientific best practices
- Stay current with advances in machine learning, generative AI, AI agents, evaluation methods, and cloud AI platforms
- Develop and evaluate machine-learning and generative-AI approaches for defined customer and platform problems
- Build model prototypes, experiments, and evaluation harnesses
- Improve AI quality, accuracy, relevance, reliability, latency, and cost through disciplined experimentation
- Apply appropriate methods for data preparation, validation, testing, and model assessment
- Work with product managers and customer stakeholders to understand use cases and translate them into measurable AI objectives
- Incorporate customer feedback into model evaluation and iterative solution improvements
- Help distinguish customer-specific needs from reusable AI platform capabilities
- Clearly communicate experimental findings, tradeoffs, limitations, and recommended next steps
- Partner with engineering teams to integrate models and AI workflows into secure, scalable cloud services
- Contribute to monitoring and evaluation approaches for production AI behavior and quality
- Help identify and mitigate risks related to model reliability, data quality, safety, privacy, and security
- Support incident analysis and continuous improvement for deployed AI capabilities
Skills
- Applicants are required to read, write, and speak the following languages: English
- 5+ years of relevant industry, research, or applied-science experience, or an advanced degree with relevant practical experience
- Master's degree or PhD in Computer Science, Machine Learning, Data Science, Statistics, Applied Mathematics, Physics, Engineering, Natural Sciences, or a related discipline; equivalent experience will be considered
- Experience applying machine learning, statistical modeling, data science, or generative AI to real-world problems
- Strong programming skills in Python and familiarity with common data-science and machine-learning libraries
- Experience with one or more of the following: Generative AI, large language models, prompt engineering, RAG, AI agents, or MCP Model training, fine-tuning, inference, evaluation, benchmarking, or model harnesses Data engineering, data platforms, data pipelines, or large-scale data analysis Applied natural-sciences research, scientific computing, laboratory systems, or research-data workflows
- Ability to design structured experiments, interpret results, and communicate recommendations clearly
- Experience collaborating with software engineers and product managers to deliver practical, production-ready solutions
- Ability to independently own moderately complex scientific workstreams while seeking guidance on broader strategy and novel research directions
- Experience with OCI Generative AI, Oracle Cloud Infrastructure, or another major cloud AI platform
- Experience with model-serving frameworks, vector databases, embedding models, orchestration frameworks, or AI-agent tooling
- Experience evaluating LLM-based systems for correctness, groundedness, safety, latency, and cost
- Experience with scientific research organizations, laboratory environments, regulated industries, or complex enterprise data
- Publications, patents, open-source contributions, or demonstrated technical leadership in applied AI, machine learning, or data science
Benefits
- May be eligible for bonus, equity, and compensation deferral.
- 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
- Volunteer programs
Company Overview
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