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

Build, test, and optimize Google Cloud-native applications and generative AI solutions across the software development lifecycle. Translate client needs into technical designs, develop AI-enabled features using Vertex AI, LLM APIs, prompt engineering, RAG, Python, LangChain, and vector databases, and evaluate model performance and guardrails. Collaborate with stakeholders, review engineering deliverables, manage workstreams, and mentor junior team members.

Leads AI and blockchain solution architecture for client and internal initiatives. Designs scalable architectures integrating AI, blockchain, cloud, DevOps, APIs, and automation; translates business requirements into technical designs and roadmaps; evaluates technologies and proof of concepts; manages risks and dependencies; guides delivery teams; communicates architecture decisions; and coaches architects and developers.

Develop AI-enabled software solutions for assurance platforms and client applications. Design, code, test, troubleshoot, and maintain scalable Python and API-based applications using cloud, DevOps, CI/CD, LLM, prompt engineering, and RAG technologies. Translate business requirements into technical designs, document delivery decisions, collaborate with clients and teams, review code, resolve issues, and guide junior developers.

Designs and delivers conversational and agentic AI solutions for contact centers, including virtual agents, intelligent routing, agent assist, IVR modernization, and workflow automation. Translates client needs into requirements, user flows, prototypes, and interaction designs; conducts discovery, user research, usability testing, and workflow analysis; collaborates with analytics, development, and product teams; reviews platform configurations; analyzes feedback and behavioral data; mentors junior staff; and supports client relationships and delivery workstreams.

Leads architecture and delivery of AI-powered pharmaceutical products, establishing AI-first engineering, testing, evaluation, LLMOps, security, and auditability practices. Partners with product managers and client technology stakeholders, oversees offshore data science, engineering, QA, and DevOps teams, and makes scalable platform decisions. Also directs Adobe-focused analytics initiatives involving data pipelines, statistical modeling, predictive analytics, visualization, KPI frameworks, and executive recommendations.

Develop AI and data analytics solutions for AML and sanctions clients within PwC’s Risk & Regulatory practice. Responsibilities include Python-based data analysis, designing data architectures and pipelines, creating dashboards, interpreting complex datasets, engaging stakeholders, and delivering actionable insights and tailored client solutions. The role also involves client relationship building, problem-solving, continuous improvement, and contributing to strategic business outcomes.

Leads AI engineering initiatives for tax technology, designing and deploying machine learning solutions using Python, deep learning, and NLP. Builds data pipelines, validates models, guides experimentation, and translates tax business needs into scalable production systems. Oversees complex workstreams, directs cross-functional teams, presents technical recommendations, coaches team members, and ensures solutions meet technical, client-service, policy, and responsible AI standards.

Leads multidisciplinary teams delivering AI-enabled, cloud-native applications on AWS. Oversees architecture, development, testing, deployment, modernization, platform engineering, security, reliability, and client advisory activities. Translates business objectives into technical roadmaps, guides complex engineering work, coordinates cross-functional architecture reviews, communicates delivery risks and options, and coaches teams across multiple workstreams.

Designs, builds, tests, and troubleshoots full-stack cloud-native applications on AWS. Translates client needs into technical solutions across architecture, development, testing, and delivery; builds scalable infrastructure and integration patterns; applies AI-enabled engineering methods; and supports modernization initiatives. The role also reviews technical work, mentors junior engineers, collaborates with architecture teams, and helps deliver cloud, data, and analytics solutions.

Leads AWS-native application design, development, testing, modernization, and architecture efforts. Manages technical workstreams, delivery timelines, scope, and team allocation while coaching engineers on cloud infrastructure, AI-native engineering, testing, and troubleshooting. Reviews technical designs and code, coordinates application and infrastructure activities, supports client architecture discussions, and improves delivery reliability and speed.