Top 258 Senior applied scientist Jobs in Gig Harbor, Wa

Senior Applied Scientist
Oracle —Seattle, WA
- Full-time
- Computer Science
- Master's degree
- Analysis skills
Senior Environmental Scientist
HDR —Seattle, WA
- $106,820 - $183,120 a year
- Full-time
- Analysis skills
- Driver's License
- Bachelor's degree
- Paid holidays
- Disability insurance
Senior Data Scientist (Active Secret Clearance)
Striveworks —Tacoma, WA
- $185,000 - $230,000 a year
- 6 years
- Computer Science
- Bachelor of Science
- Paid parental leave
- Health savings account
Staff Applied AI/ML Scientist
Lululemon —Seattle, WA
- $211,880 - $278,090 a year
- Full-time
- Computer Science
- Master's degree
- Bachelor's degree
- Health insurance
- Dental insurance
Senior Engineer - Applied AI
GEICO —Seattle, WA
- $100,000 - $215,000 a year
- Full-time
- Computer science
- Computer Science
- System design
4d
Senior Applied Scientist, Amazon Robotics - Vulcan
Amazon.com Services LLC —Seattle, WA
- $167,100 - $226,100 a year
- Full-time
- 6 years
- System design
- Java
- AD&D insurance
- Health insurance
Senior Applied Scientist
Amazon.com Services LLC —Seattle, WA
- $167,100 - $226,100 a year
- Full-time
- 3 years
- Java
- Master's degree
- AD&D insurance
- Health insurance
Senior Machine Learning Engineer (Active Secret Clearance)
Striveworks —Tacoma, WA
- $185,000 - $230,000 a year
- Computer science
- 6 years
- Management
- Paid parental leave
- Health savings account
Principal Applied AI/ML Scientist
Lululemon —Seattle, WA
- $266,720 - $350,070 a year
- Full-time
- Computer Science
- 11+ years
- Office
- Health insurance
- Dental insurance
Senior Manager, Product Management - CX
Qualtrics —Seattle, WA
- $253,500 - $333,000 a year
- Full-time
- Hybrid work
- Office
- Product management
- Mentoring
- Health insurance
- Dental insurance
Senior Data Scientist
Accenture —Seattle, WA
- $87,400 - $293,800 a year
- Full-time
- Hybrid work
- Azure
- 6 years
- Doctoral degree
- Paid holidays
- Disability insurance
13d
Senior Applied Scientist
Outreach —Seattle, WA
- $140,000 - $175,000 a year
- Full-time
- Computer Science
- Java
- Master's degree
- Health insurance
- Dental insurance
Senior Applied Scientist, AWS Security
Amazon.com Services LLC —Seattle, WA
- $167,100 - $226,100 a year
- Full-time
- 3 years
- Master's degree
- Doctor of Philosophy
- AD&D insurance
- Health insurance
Senior Applied Scientist , Sponsored Products
Amazon.com Services LLC —Seattle, WA
- $183,800 - $248,700 a year
- Full-time
- 6 years
- Java
- Master's degree
- AD&D insurance
- Health insurance
Principal Applied Scientist, Amazon Payments
Amazon.com Services LLC —Seattle, WA
- $198,900 - $269,000 a year
- Full-time
- Computer science
- Computer Science
- Doctor of Philosophy
- AD&D insurance
- Health insurance
Senior Research Scientist, Survey Methods, Amazonian Leadership Experience
Amazon.com Services LLC —Seattle, WA
- $159,200 - $215,300 a year
- Full-time
- 5 years
- Master's degree
- AWS
- AD&D insurance
- Health insurance
Senior Machine Learning Scientist
Expedia —Seattle, WA
- $173,000 - $299,000 a year
- Full-time
- Computer Science
- 3 years
- Master's degree
- Health insurance
- Dental insurance
Applied Scientist, Prime Video
Amazon.com Services LLC —Seattle, WA
- $142,800 - $193,200 a year
- Full-time
- Mid-level
- Java
- Master's degree
- AD&D insurance
- Health insurance
Senior Applied Scientist, Sponsored Products Bidding
Amazon.com Services LLC —Seattle, WA
- $183,800 - $248,700 a year
- Full-time
- 6 years
- Java
- Master's degree
- AD&D insurance
- Health insurance
Senior Applied Scientist, Featured Merchant Algorithm
Amazon.com Services LLC —Seattle, WA
- $167,100 - $226,100 a year
- Full-time
- 6 years
- Java
- Master's degree
- AD&D insurance
- Health insurance

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Senior Applied Scientist

Oracle -
Seattle, WA

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Job Details

Full-time

Qualifications

AI models
Software engineering
Quantitative applied research
Cloud infrastructure
Defect resolution root cause analysis
Qualitative data analysis
Software coding
Design of experiments
Testing and evaluation
Generative models
Reliability analysis
AI platforms (beyond public GPTs)
Computational framework
Research project design
Machine intelligence
Machine learning libraries
Model evaluation
Machine learning frameworks
Generative AI
Cross-functional communication
Data analysis software
Failure analysis
Scientific reports

Full Job Description

The OCI AI Evaluation Science team builds the evidence behind model-selection, product-readiness, and launch decisions. We evaluate frontier foundation models and AI systems across capabilities such as reasoning, coding and agentic coding, retrieval-augmented generation, AI agents, NL2SQL, multimodal understanding, multilingual performance, and responsible AI.

As a Senior Applied Scientist on the team, you will independently own complex evaluation work from problem definition, benchmark development, and final recommendation to executive leadership. You will translate ambiguous product and customer questions into measurable hypotheses, select or create appropriate benchmarks, design experiments, build evaluation pipelines, validate data and metrics, analyze failure modes, and communicate conclusions to science, engineering, product, and leadership stakeholders.

This is hands-on applied science. You will write high-quality code, work with large and imperfect datasets, develop and calibrate automated evaluators, and turn one-off analyses into reproducible evaluation protocols and reusable infrastructure. You will examine more than aggregate benchmark scores, considering factors such as statistical validity, data provenance, contamination, robustness, cost, latency, reliability, safety, and operational constraints.

The work sits at the point where research results become product decisions. Success requires scientific rigor, strong engineering judgment, clear writing, and the ability to make progress when requirements, model access, data, or infrastructure are still evolving. You will collaborate closely with other scientists, software engineers, product teams, data and human-annotation teams, and external partners to deliver evaluation results that are technically defensible and useful in practice. You will develop novel benchmarks and evaluation methodologies that are publishable at top tier AI conferences.

Key Responsibilities

Independently own end-to-end evaluations of foundation models, AI agents, and enterprise AI systems, from initial question and experiment design through analysis, reporting, and stakeholder review.
Translate customer, product, and business needs into testable hypotheses, evaluation criteria, datasets, metrics, baselines, and acceptance thresholds.
Design, implement, and maintain benchmarks and evaluation methods for areas such as but not limited to reasoning, coding, agentic workflows, RAG, NL2SQL, multimodal systems, multilingual performance, and responsible AI.
Publish original research in top-tier peer-reviewed conferences and journals, and translate relevant evaluation advances into reusable methods, technical reports, or production capabilities for OCI.
Write production-quality evaluation code; build reproducible pipelines, test suites, automated checks, and integrations with shared evaluation platforms.
Evaluate model and system behavior across quality, cost, latency, reliability, safety, robustness, and domain fit rather than relying only on aggregate scores.
Conduct statistical analysis, error analysis, ablations, and qualitative failure-mode investigations to explain model behavior and identify meaningful differences between systems.
Develop and validate automated evaluators, including LLM-as-a-judge and VLM-as-a-judge methods; calibrate them against human judgments and quantify their reliability, bias, and limitations.
Design human-evaluation and annotation workflows, including rubrics, gold datasets, sampling plans, quality controls, and vendor or Human-in-the-Loop validation.
Assess dataset quality, provenance, representativeness, contamination risk, licensing constraints, privacy, and other factors that could invalidate an evaluation or limit use of its results.
Produce concise, decision-ready reports that make methods, assumptions, limitations, tradeoffs, and recommendations explicit for technical and non-technical audiences.
Partner with science, engineering, product, data, and operations teams to define requirements, resolve blockers, manage dependencies, and establish clear handoffs and ownership.
Turn successful evaluation work into reusable protocols, documented workflows, and shared infrastructure that improve the speed and consistency of future evaluations.
Stay current with research in machine learning, generative AI, agent evaluation, and measurement methodology; prototype promising approaches and contribute to science plans, papers, patents, or technical reports where appropriate.
Review technical work, share expertise, and mentor junior scientists or engineers in experimental design, evaluation methodology, coding, and interpretation of results.

Minimum qualifications

PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, or a related quantitative field; or a Master’s/Bachelor’s degree with equivalent relevant industry experience.
Experience designing and executing machine learning experiments, including defining hypotheses, selecting datasets and metrics, establishing baselines, and interpreting results.
Strong knowledge of modern machine learning, deep learning, natural language processing, and generative AI methods.
Hands-on experience evaluating large language models, foundation models, AI agents, or other machine learning systems.
Proficiency in Python and experience writing reliable, maintainable code for experiments, data processing, or machine learning systems.
Experience working with machine learning frameworks and data-science libraries such as PyTorch, TensorFlow, Hugging Face, NumPy, pandas, or equivalent tools.
Demonstrated ability to build and analyze complex datasets, identify data-quality problems, and perform statistical, error, and failure-mode analysis.
Experience translating technical findings into clear written recommendations for science, engineering, product, or business stakeholders.
Ability to work independently on complex assignments while collaborating effectively with scientists, engineers, product managers, and other cross-functional partners.
Experience operating machine learning components in cloud environments.
Strong written and verbal communication skills.

Preferred qualifications

Publications in top-tier machine learning, natural language processing, computer vision, data mining, or artificial intelligence conferences or journals.
Experience building evaluation frameworks, benchmarks, test suites, or observability systems for generative AI models and applications.
Experience evaluating one or more of the following: AI agents, agentic coding systems, RAG, NL2SQL, multimodal models, multilingual models, reasoning systems, or responsible AI capabilities.
Experience developing or calibrating LLM-/VLM-as-a-judge methods against human judgments.
Experience designing human-evaluation programs, including annotation rubrics, sampling plans, gold datasets, inter-annotator agreement analysis, and quality-control processes.
Experience converting research prototypes or one-off experiments into reusable, production-quality tools and workflows.
Familiarity with model-evaluation concerns such as benchmark contamination, data provenance, robustness, statistical significance, safety, latency, cost, and reproducibility.
Experience working with distributed computing, large-scale datasets, model serving, or parallel evaluation workloads.
Demonstrated ability to identify new research questions, develop novel evaluation methods, and translate research advances into practical capabilities.
Familiarity with enterprise AI requirements, including privacy, security, licensing, compliance, reliability, and auditability.

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Refine Your Search

senior applied scientist jobs in gig harbor, wa

Senior Applied Scientist

Senior Environmental Scientist

Senior Data Scientist (Active Secret Clearance)

Staff Applied AI/ML Scientist

Senior Engineer - Applied AI

Senior Applied Scientist, Amazon Robotics - Vulcan

Senior Applied Scientist

Senior Machine Learning Engineer (Active Secret Clearance)

Principal Applied AI/ML Scientist

Senior Manager, Product Management - CX

Senior Data Scientist

Senior Applied Scientist

Senior Applied Scientist, AWS Security

Senior Applied Scientist , Sponsored Products

Principal Applied Scientist, Amazon Payments

Senior Research Scientist, Survey Methods, Amazonian Leadership Experience

Senior Machine Learning Scientist

Applied Scientist, Prime Video

Senior Applied Scientist, Sponsored Products Bidding

Senior Applied Scientist, Featured Merchant Algorithm

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