Top AI Specialist Jobs in Seattle, WA

PhD-level physicists will design challenging graduate-level physics problems and contribute high-quality datasets to improve AI model reasoning, ensuring scientific rigor and consistency while collaborating remotely and asynchronously.

The AI/Machine Learning Specialist designs and implements AI solutions, collaborates with cross-functional teams, and continuously improves ML processes.

Lead complex, cross-functional AI programs end-to-end: translate strategy into integrated plans, drive multi-team execution, mitigate risks (data, model, compliance), apply ML lifecycle practices, use Agile/kanban methods, manage budgets/vendors, communicate to senior stakeholders, and mentor other program managers to improve AI program standards.

Assess AI-enabled products and software against regulatory requirements and standards, supporting conformity assessments, CE marking, certification, and client guidance. Review technical documentation, mentor colleagues, develop assessment procedures and tools, contribute to AI testing methodologies, and support accreditation, quality, and continuous improvement activities. The role requires practical AI/ML experience, regulatory knowledge, strong analytical skills, and collaboration across global multidisciplinary teams.

Author and verify rigorous multiple-choice computer science assessment items across many CS domains to create gold-standard benchmarks for AI research. Produce correct answers, nine plausible distractors, solution explanations, difficulty labels, and authoritative references. Review and edit questions for technical accuracy, clarity, and reproducibility. Contribute asynchronously as an independent contractor, ~10+ hours/week, fully remote.

The Data Scientist will develop data labeling strategies, optimize datasets for LLMs, analyze data quality, and collaborate with engineering on data processing pipelines.

Review, localize, translate, fact-check, and adapt football-related content from English (US) to Dutch, following style guides. Perform quality control, MT post-editing and evaluations, conduct market-specific research, and provide feedback to improve localized content for Dutch audiences.

Optimize and compress large language and vision models for on-device inference. Build model distillation and hardware-specific compilation pipelines, and benchmark performance across various NPU/GPU architectures to enable efficient edge deployment.

Develop intent-recognition models from gaze, gesture, and voice data; implement socially aware navigation that respects personal space; and design visual and auditory feedback for robot user interfaces. Run user studies and rapidly prototype AI-driven voice and visual interfaces.

Design and implement high-fidelity spatial mapping and real-time object recognition pipelines; integrate vision outputs with robotic manipulation and navigation systems; and train and fine-tune Vision-Language-Action models to improve robotic autonomy and perception.

Perform adversarial testing on language models and multimodal agents, implement guardrails and real-time filters for autonomous tools, and develop constitutional AI principles and RLHF alignment pipelines to ensure safe AI deployment.

The role involves designing and delivering AI training programs, creating learning materials, and facilitating workshops to enhance user understanding of AI tools within enterprises.

Design, develop, and deploy Agentforce AI agents and custom actions on the Salesforce platform. Build Apex classes, LWCs, flows, and API integrations with Data Cloud and legacy federal systems. Enforce AI safety, federal security/compliance, support testing/UAT, and enable secure DevSecOps/CI/CD deployments in cleared environments.

Design, develop, and deploy Agentforce AI agents and custom actions on Salesforce. Build Apex, LWCs, flows, and secure API integrations with legacy federal systems and Data Cloud. Ensure AI safety, compliance, testing, and support CI/CD/DevSecOps practices in cleared federal environments.

The AI Adoption Specialist guides organizations in integrating AI technologies, developing strategies, conducting pilots, and overseeing deployment while monitoring performance.

Embed with business teams to design and build AI-powered tools, automations, and workflows; coach and enable staff; create reusable solutions, documentation, adoption metrics, and governance; mentor junior members and translate AI developments into practical enterprise applications.

Develop, test, and maintain applications using Java, Python, or Node.js. Write clean, efficient code, debug and optimize, collaborate with cross-functional teams, use data structures/algorithms, work with SQL/NoSQL databases, participate in code reviews, and stay current on AI/ML concepts, agents, and automation tools.

Sell coding-assistant and AI-native engineering solutions and co-sell NVIDIA developer-platform optimizations. Engage enterprise development leadership, design pilots and benchmarking services, scope consulting engagements, and collaborate within regional PODs to drive AI-accelerated application performance and developer productivity.

Perform on-site data annotation and quality assurance for natural language datasets, test AI products, analyze data for consistency and model performance, report anomalies and insights, and collaborate to refine machine learning models.