Top AI Specialist Jobs in San Francisco Bay Area, CA

Own clinical quality for member-facing AI products by partnering with product, engineering, and clinical teams. Design clinical AI evaluations, define quality thresholds and rubrics, assess accuracy, omissions, hallucinations, medication-safety risks, and translate clinical reasoning into prompts and decision logic. Monitor evolving evidence and standards of care, validate product launches, and communicate findings to technical and clinical audiences.

Design, develop, and maintain enterprise AI applications, including conversational assistants, copilots, autonomous agents, RAG solutions, and workflow automation. Build scalable APIs and microservices integrating foundation models and enterprise systems. Apply prompt and context engineering, memory management, observability, governance, and performance optimization. Collaborate with cross-functional teams to identify automation opportunities and participate in Agile development, code reviews, CI/CD, and DevSecOps.

Create precise vector annotations and segmentation masks on geospatial imagery, validate and correct automated detections, maintain documentation and QA, support dataset pipelines, and assist ML teams with inference and model evaluation to produce production-ready training data.

Lead AI Governance initiatives with strategic customers, translate customer insights and regulations into product vision and roadmap, guide development of AI inventories, risk management, policy and governance workflows, influence product and engineering execution, drive adoption and measurable business outcomes, and act as trusted advisor on responsible AI and compliance.

Design and build AI- and automation-driven solutions to accelerate Mortgage Cadence Platform configuration using LLMs and workflow automation. Develop integrations with system APIs, partner with implementation teams, create documentation and training, and propose new tools to improve implementation accuracy and scale.

Provide insurance subject-matter expertise to improve generative AI models: design insurance tasks, create reference solutions, evaluate AI outputs with structured rubrics, refine scoring guidelines, and collaborate with research and engineering teams to produce high-quality training and evaluation data. Commitment of 35+ hours/week and proven senior insurance experience required.

Design and run red-team evaluations to find failure modes and edge cases in frontier LLMs. Create reproducible, multi-step benchmark tasks, document technical findings, and collaborate with researchers to refine grading and improve model robustness. Commit ~35 hours/week as a remote independent contractor.

Evaluate and improve LLM financial reasoning by designing real-world finance tasks, creating reference solutions, scoring AI outputs with structured rubrics, refining evaluation frameworks, and collaborating with researchers to raise data quality and model performance. Must provide detailed feedback and identify gaps to enhance AI across finance use cases.

Lead design, validation, and continuous improvement of AI-assisted measurement and learning systems for K-12 assessments. Translate measurement intent into reproducible AI workflows, prototype AI-assisted content generation, ensure outputs meet validity, fairness, accessibility, and instructional standards, design validation and monitoring frameworks, partner with cross-functional teams (AI Science, Technology, Content), and contribute research, documentation, and thought leadership on intelligent assessment and learning systems.

Design, build, and deploy production AI systems and integrations (LLM-based) for law-firm clients. Create connectors, automation workflows, agents, and enablement programs, embed AI into client processes, and support internal AI adoption.

Design realistic, specialty-specific clinical case scenarios and gold-standard attending-level responses, evaluate and grade AI-generated outputs using structured rubrics, provide detailed written feedback to improve model clinical reasoning, and participate in onboarding, calibration, and review sessions in a fully remote, asynchronous contractor role (~20 hours/week).

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.

As a Training Specialist, you'll design and deliver training materials for expert contributors in AI data labeling, ensuring high-quality output through effective onboarding and skill development.

Work with product, engineering, and data teams to generate, label, and evaluate medication-focused datasets, review AI outputs for clinical accuracy, provide SME guidance for product features, ensure safety/compliance, and improve clinical intelligence processes and tooling.

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.

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.

Own end-to-end customer onboarding: scope integrations, build and deploy integrations against real customer data, diagnose extraction or pipeline issues, drive adoption and expansion, and act as the technical voice between customers, product, and engineering to shorten time-to-value.

Design, deploy, and operate large-scale LLM and multimodal inference architectures. Work hands-on with customer engineering teams to containerize, scale, monitor, and troubleshoot GPU-based inference workloads across Kubernetes, CI/CD, and hybrid/on-prem environments. Create Helm charts, Terraform modules, and observability tooling while delivering workshops and platform reliability insights.

Lead presales technical engagements for Anaplan's AI-infused planning platform. Architect AI solutions, run technical discovery, build demos/POCs and workshops, collaborate with product and sales, and drive AI-focused opportunities to close with enterprise customers.

Design and implement high-fidelity spatial mapping and real-time object recognition pipelines. Integrate vision systems with robotic manipulation and navigation controls. Train and fine-tune Vision-Language-Action models and work with multimodal spatial AI frameworks and robotic hardware.

Develop multimodal intent-recognition models from gaze, gesture, and voice; implement socially aware navigation respecting personal space; design robot visual and auditory UI feedback; run user studies and rapidly prototype AI-driven voice and visual interfaces.

Run adversarial tests on language and multimodal models, build guardrails and real-time filters for autonomous tool use, and support RLHF alignment and constitutional AI development to ensure safe AI deployment.