Top AI & Machine Learning Jobs in New York City, NY

The role involves collaborating with teams to develop AI-powered products, leveraging NLP and LLM technologies while operationalizing models into production systems.

Lead AI Engineer to design, build, deploy, and support production-scale vision and foundation-model components (training, inference, vector search, guardrails, evaluation, observability). Partner with cross-functional teams, optimize LLM training/inference for cost/latency/throughput, and help set the technical vision and roadmap for foundational AI systems at Capital One.

Design, develop, deploy, and support foundational AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, observability). Optimize training/inference for scalability, cost, latency, and throughput. Partner cross-functionally to deliver production AI services and shape the technical vision and roadmap for foundational AI at scale.

Lead model validation and risk quantification across business domains. Partner with data scientists, engineers, and PMs to build and challenge production models using Python, Spark, H2O, and cloud tools. Drive model governance, backtesting, and present identified model risks to executives while mentoring teams and advancing validation frameworks.

Lead design, develop, test, deploy, and support foundational AI systems including foundation model training, LLM inference, similarity search/VectorDBs, guardrails, evaluation, observability, and optimization for scalability, cost, latency, and throughput. Partner cross-functionally and contribute to technical vision and roadmap.

Lead modernization of enterprise AI/ML infrastructure and analyst workflows. Build agentic, scalable, secure platform services, integrate generative AI and low-code/no-code tooling, scale AutoML for tabular and time-series, and engineer automated governance and controls while mentoring teams and influencing cross-functional stakeholders.

Lead a cross-organizational program to transition engineering to an AI-driven, self-optimizing ecosystem with robust telemetry and evaluation. Orchestrate strategy and execution, mitigate technical risk, build and grow a TPM practice, align product/engineering/design/data science, and deliver measurable business impact.

Lead development and productionization of scalable ML models and infrastructure. Design ML architectures, build data pipelines, deploy and monitor models, ensure CI/CD, governance, and collaborate with cross-functional Agile teams.

Lead Enterprise AI product strategy for Associate Experience, unify AI initiatives, set governance and roadmaps, drive adoption via enablement and standardized interaction patterns, and manage cross-functional alignment and a product team integrating AI agents and core services.

Lead design, development, deployment, and support of scalable GenAI platform components (foundation model training, LLM inference, vector search, guardrails, evaluation, observability). Optimize training and inference performance, contribute to technical vision and roadmap, and partner with cross-functional teams to deliver responsible, production-grade AI systems.