Top AI & Machine Learning Jobs

Lead research on LLM mid-training, post-training, and agentic architectures. Develop experimentation harnesses, evaluation benchmarks, and methodologies for reasoning, planning, tool use, reliability, factuality, and safety. Investigate model failures, formulate novel research hypotheses, conduct rigorous experiments, and transition validated approaches into production. Communicate results through publications, patents, open-source contributions, and collaboration with engineering and executive stakeholders.

Own the architecture, safety, evaluation infrastructure, and production quality of agentic and conversational AI capabilities for HR workflows. Define autonomy boundaries, prompts, tools, context handling, model migrations, evaluation datasets, CI gates, observability, and access controls. Partner with product, engineering, and design while contributing to complex integrations, incident response, and architectural prototypes. The role requires hands-on experience with LLM APIs, retrieval, orchestration, tool calling, structured outputs, entitlement-aware data, and AI-assisted engineering.

Owns the technical architecture, safety boundaries, evaluation infrastructure, and production standards for HR-focused agentic and conversational AI. The role defines orchestration, context, tools, prompts, model migrations, access controls, observability, testing, and drift detection. It partners cross-functionally, handles complex integrations and incidents, and sets standards for AI-assisted engineering. Hands-on experience with LLM APIs, retrieval, tool calling, structured outputs, Java, JavaScript/TypeScript, and React is required.

Owns the architecture, standards, safety boundaries, and evaluation infrastructure for agentic and conversational AI capabilities in the HR domain. Responsibilities include LLM orchestration, retrieval, tool calling, access-controlled data handling, evaluation suites, observability, migration strategy, production quality, and incident response. The role partners cross-functionally, establishes AI-assisted engineering standards, and provides hands-on technical leadership for complex integrations and customer-facing systems.

Owns the architecture, standards, safety boundaries, and evaluation infrastructure for AI agents and conversational experiences in ServiceNow’s HR domain. Responsibilities include model and orchestration decisions, prompt and tool governance, entitlement-aware retrieval, evaluation suites, production observability, incident response, and AI-assisted engineering standards. The role partners across product, engineering, and design while remaining hands-on with complex integrations and migrations.

Leads advanced AI research on enterprise agentic systems, focusing on tacit knowledge, continual learning, resilience, safety, threat detection, privacy, and responsible AI. Defines research agendas, publishes influential work, validates hypotheses against deployed systems, and provides scientific leadership across research, engineering, and product teams. Requires strong software development, technical influence, and communication skills.

Build scalable full-stack engineering infrastructure for AI-powered, agentic content creation and knowledge delivery. Responsibilities include developing automation pipelines, LLM integrations, reusable software, cloud production systems, and modern web applications. The role owns design through delivery, partners with product owners, improves existing products, manages technically complex projects, drives cross-functional initiatives, mentors engineers, and promotes strong engineering practices including testing, code reviews, observability, and scalable architecture.

Design, build, and operate production-grade agentic AI systems for ServiceNow’s enterprise platform. Responsibilities include multi-agent orchestration, tool use, planning, memory, retrieval and grounding, model integration, evaluation, safety governance, observability, and failure recovery. The role requires ownership of scalable system and database architecture, technical leadership, architecture decisions, code reviews, mentoring, and stakeholder communication.

Provides technical vision and architecture for AI-native and cloud-native systems at organizational scale. Leads development of AI platforms, evaluation and monitoring frameworks, retrieval pipelines, security guardrails, and distributed systems. Drives ServiceNow platform strategy, technical roadmaps, architectural standards, production reliability, and responsible AI practices. Mentors senior engineers and leaders, influences executives and cross-functional teams, supports strategic customers, leads complex technical initiatives, and contributes to critical software development and innovation.

Owns technical relationships with enterprise customers, designing and implementing AI solutions on the Moveworks Platform. Responsibilities include architecture, API integrations, workflow automation, customer advisory, implementation leadership, product feedback, and reusable solution development. The role requires frequent customer engagement, executive communication, collaboration with engineering and product teams, and travel up to 25%.