Top AI Specialist Jobs in NYC, NY

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.

Drives AI adoption across IRC’s global operations by identifying and prioritizing use cases, defining requirements, coordinating development, supporting testing and deployment, redesigning workflows, and leading sustained user adoption. The role manages an AI opportunity pipeline, measures impact, develops training and communications, supports end users, and scales successful solutions across Finance, Supply Chain, HR, and other functions.

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.

Develop data-driven insights, predictive models, and analytical tools for U.S. Rates trading. Build dashboards and applications, leverage AI/agentic tools and ML techniques, partner with product and sales, and identify revenue-generating data products to drive strategy and improve client outcomes.

Provide escalated technical support and troubleshoot logs, APIs, and integrations while working with agentic AI infrastructure to improve resolution quality. Coordinate with Engineering and Product on incidents, maintain knowledge base, track recurring issues, and help onboard new team members.

Conduct research on machine learning algorithms, implement and validate these algorithms, collaborate in a multidisciplinary team, and publish findings.

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.

Lead identification, prioritization, and delivery of production-grade AI and generative AI solutions for reinsurance operations. Drive AI strategy, cross-functional execution, governance and responsible AI, change management, training, and measurable business value.

Lead identification, design, and delivery of generative AI solutions across reinsurance operations. Drive AI strategy, cross-functional coordination, MLOps productionization, responsible AI governance, change management, and stakeholder adoption to deliver measurable business value.

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.

Support HR&A Labs by performing geospatial and economic data analysis, building interactive dashboards and web tools, maintaining data systems, and contributing to client-facing deliverables. Work includes procuring/cleaning large datasets (census, PUMS), prototyping products with AI tools, and gradually owning analytics workstreams.

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.

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.

As an AI Product Specialist at Kensho, you will drive market expansion, manage customer engagement, and leverage AI product strategies while collaborating across teams to ensure effective go-to-market execution for AI solutions.

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.