Legal Advisor (US Bar Admitted) - Freelance AI Trainer
Contributors may generate prompts that challenge AI; evaluate AI-generated solutions for correctness, assumptions, and logic; improve AI reasoning to align with first principles and accepted standards; and apply structured scoring criteria to assess multi-step problem solving.
Legal Advisor (US Bar Admitted) - Freelance AI Trainer
Contributors may generate prompts that challenge AI; evaluate AI-generated solutions for correctness, assumptions, and logic; improve AI reasoning to align with first principles and accepted standards; and apply structured scoring criteria to assess multi-step problem solving.
Legal Advisor (US Bar Admitted) - Freelance AI Trainer
Contributors generate prompts that challenge AI, evaluate AI-generated solutions for correctness, assumptions, and logic, improve AI reasoning to align with first principles and accepted standards, and apply structured scoring criteria to assess multi-step problem solving.
Legal Advisor (US Bar Admitted) - Freelance AI Trainer
Contributors may generate prompts that challenge AI; evaluate AI-generated solutions for correctness, assumptions, and logic; improve AI reasoning to align with first principles and accepted standards; and apply structured scoring criteria to assess multi-step problem solving.
Optical Engineer - Freelance AI Trainer
Contributors may design original optics problems that simulate real physics research workflows, ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes, develop problems requiring non-trivial reasoning chains in mechanics, electromagnetism, thermodynamics, and quantum mechanics, base problems on real research challenges or practical applications from optics and physics practice, and document problem statements clearly with verified correct answers.
Client Engineering Lead
As a Staff/Principal-level Technical Lead, you will be responsible for driving the end-to-end technical execution of multiple concurrent enterprise engagements in close partnership with the Project Lead, from technical discovery to production deployment. You will architect and implement secure, highly scalable integrations between the AI platform and clients' existing data pipelines, APIs, and infrastructure. You will lead technical discovery sessions, architecture workshops, and data readiness assessments with customer IT, data, and engineering leadership teams. You will build and customize AI-enabled solutions, scripts, and workflows that address complex business problems identified in the sales process. You will serve as the primary technical liaison and escalation point between customer engineering teams and internal product, engineering, and data science teams to unblock deployments quickly. You will ensure that all deployed solutions meet enterprise-grade standards for performance, security, data privacy, and scalability. You will debug complex integration issues, manage technical risks across overlapping projects, and provide hands-on troubleshooting during implementation. Additionally, you will contribute to the internal codebase by documenting technical blueprints, developing reusable integration components, and providing product feedback based on real-world edge cases.
Supervisor, HCS Specialty Recovery
Design agent systems from first principles by deciding the loop, tools, context strategy, and evaluation method, choosing between different architectural approaches and defending choices with data; engineer the context including prompt design, context windows, tool surfaces, structured outputs, and citation grounding; drive evaluation rigor by building evaluations prior to agent development, diagnosing failures, fixing root causes, and proving improvements; use AI tools such as Claude Code and Codex extensively for planning, scaffolding, refactoring, and debugging; and become a domain expert in healthcare claims, coding guidelines, and medical records to contribute effectively.
Sr. Director | Engineering, ML
Design agent systems from first principles including deciding the loop, tools, context strategy, and evaluation. Choose between single-agent and multi-agent topologies, LLM reasoning and deterministic post-passes, and retrieval versus direct context loading, defending these choices with data. Engineer the context by focusing on prompt components such as context windows, tool surfaces, structured outputs, citation grounding, and the prompt itself. Drive evaluation rigor by building evaluations prior to agent development, diagnosing failures, fixing root causes, and proving metric improvements. Use AI tooling extensively for planning, scaffolding, refactoring, and debugging your work. Become a domain expert in healthcare claims, coding guidelines, and medical records to contribute significantly within the domain.
Senior Customer Success Manager
Own the implementation of AI agents including prompt design, workflow configuration, integrations, telephony setup, and evaluation frameworks. Act as the primary technical partner for customers by leading regular demos, communicating progress, gathering feedback, and guiding solutions from concept to production. Configure and connect systems using APIs, handling authentication, data mapping, error handling, and integrations with CRMs, knowledge bases, and other enterprise tools. Set up SIP/CCaaS/PSTN routing, pass metadata, configure fallbacks, and troubleshoot call quality. Write and refine prompts for LLM-driven agents, monitor performance, test iteratively, and ensure agents meet automation and containment targets. Translate customer requirements into actionable solutions and work consultatively to unblock challenges in security, connectivity, or knowledge ingestion. Collaborate with product and engineering teams to escalate platform gaps and resolve technical fixes and platform issues while independently driving leading client implementations.
Senior Software Engineer, Computer Vision
Design, build, implement and optimize multi-stage computer vision pipelines that span segmentation, object detection, multimodal LLM/LVM extraction, machine-readable code decoding, and multi-source reconciliation. Train or fine-tune detection models on custom medical supply datasets. Build and own dataset strategy including leveraging augmentation and synthetic data generation to improve training and testing datasets when data is scarce. Monitor and improve pipeline accuracy by instrumenting field-level metrics, diagnosing failure modes, and systematically improving precision and recall through model iteration and preprocessing optimization. Design persistence schemas and audit data models to ensure every data extraction is independently reviewable. Maintain and extend asynchronous Python backend services that provide pipeline results to downstream clinical workflows.
Access all 4,256 remote & onsite AI jobs.
Frequently Asked Questions
Need help with something? Here are our most frequently asked questions.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.