Top AI Specialist Jobs in NYC, NY

Build, tune, and QA conversational AI agents on the Regal platform: design prompts and flows, tune STT/LLM/TTS settings, create custom functions, test agents, codify best practices, and provide product feedback and sales demos.

Drive market expansion and adoption of Kensho's AI products by bridging technical AI capabilities and commercial strategy. Lead go-to-market planning, customer demos, co-development partnerships, market analysis, sales enablement, and cross-functional alignment to translate customer needs into product and roadmap priorities.

Annotate 3D wire spans and identify visualization errors in LiDAR/camera datasets using internal tools. Maintain data integrity, document anomalies, collaborate with engineers, QA, and field techs, and deliver accurate datasets for utility infrastructure projects.

Lead AI adoption strategy and communications across the CIB, design and deliver upskilling and change management programs, partner with L&D and business units to close capability gaps, define success metrics, use data to drive adoption decisions, and oversee enablement of AI tools across sub-lines of business.

Lead development of next-generation entity resolution using transformers, graph ML, and deep learning at scale. Partner with engineers and product to design, train, validate, and deploy models on AWS/Spark, leverage agentic AI workflows, and translate technical work into business impact across enterprise use cases.

Lead development of next-generation entity resolution solutions using transformers, graph ML, deep learning, and big-data tooling. Partner with engineers and product to design, train, evaluate, validate, and deploy ML models at scale; leverage Agentic AI workflows; translate technical work into business impact across enterprise use cases.

Design and run advanced analyses and machine learning/NLP models on large multimodal mental-health datasets. Build preprocessing, feature engineering, validation, and visualization pipelines; write scalable documented code for HPC environments; use version control and containerization; collaborate on project planning and present scientific findings while responsibly handling sensitive data.

Design, build, test, deploy, monitor, and maintain production LLM-based agentic solutions for Commercial Customer Success. Integrate agents with CRMs and Samsara systems, define evaluation frameworks and success metrics, implement automated tests and monitoring, iterate on models and prompts, and demonstrate impact on customer outcomes and retention.

Lead go-to-market and technical strategy for AI developer tooling, winning early customers and building repeatable playbooks. Translate customer MLOps requirements into product feedback, partner with engineering and Weights & Biases, and enable sales/solutions teams to close deals around experiment tracking, model governance, and LLM observability.

Sell and shape adoption of CoreWeaves AI Runtime Services by driving technical-commercial strategy, proving value with early customers, creating playbooks, and feeding product roadmap. Advise on serving frameworks, batching, execution isolation, throughput modeling, GPU utilization, and SLA structures while partnering with product, infra, and sales teams.

Lead development of next-generation entity resolution ML solutions using transformers, graph ML, and large-scale data pipelines. Partner with cross-functional teams to design, train, validate, and deploy models on cloud platforms, leverage agentic AI workflows, and translate technical work into business outcomes.

Apply advanced analytics and ML to climate risk and resilience projects: process large geospatial and climate datasets using Python and Pangeo tools, build scalable cloud workflows, design and validate statistical and ML models, produce climate risk tools and client-facing reports, and support multidisciplinary teams in delivering reproducible solutions.

Compare source texts with Hebrew machine translations to judge accuracy, grammar, and naturalness. Make simple pass/fail quality assessments following provided guidelines. Weekly commitment 1–5 hours for a year; no rewriting required.

Test and validate AI solutions, log and troubleshoot issues, create test plans and customer-facing documentation, refine documentation processes, collaborate with cross-functional teams, and train new Product Specialists.

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.

Drive company-wide adoption of AI tools and workflows: design and deliver training, provide hands-on support, monitor adoption, build documentation and playbooks, pilot AI-assisted features with product teams, and present impact findings to stakeholders.

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.

Designs, builds, tests, and deploys AI-enabled automations and copilots for GTM and RevOps. Creates reusable agent templates, prompt libraries, and orchestration patterns; implements end-to-end API integrations; monitors performance; documents and hands off production solutions; and trains/coaches business teams on safe, responsible AI usage and prompting best practices.

The role involves cultivating technical relationships with Accenture, supporting solution development, customer deal support, and representing Databricks at events.

Lead design and implementation of AI and data governance frameworks, privacy guardrails, metadata standards, and compliance with GDPR/HIPAA/CCPA/NIST AI RMF. Monitor and audit models for bias, explainability, and transparency; partner with engineers, stewards, and leaders to embed ethical decision-making, set KPIs, run audits, and produce dashboards and reports to drive governance adoption.

Review machine-translated content into Finnish by comparing source and translation, making pass/fail quality judgments on accuracy, grammar, and naturalness. Follow guidelines and provide consistent assessments during a one-year, 1–5 hour/week freelance engagement.

Create, optimize, schedule, and publish blog and social content about AI applications. Test headlines, landing pages, and ads; review analytics, predict opens/clicks/conversions, write performance reports, and personalize curated content.

Design and maintain a skill and concept graph, build ML models to infer learner skills, and develop recommendation systems and LLM-driven features. Ship production-ready LLM systems, define explainability standards, partner with frontend and product teams, and monitor model performance and evaluation frameworks.

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