Top Artificial Intelligence Jobs

Lead product strategy for GenAI safety across Pinterest: build proactive safety frameworks, run threat modeling and red-teaming, translate policy into product requirements, define safety metrics, manage incident response, and collaborate cross-functionally to ensure equitable, scalable AI safeguards.

Partner with corporate functions to discover AI automation opportunities, design end-to-end agentic AI solutions, build production-quality Python services with CI/CD, monitoring and guardrails, pilot and drive adoption, ensure responsible data handling, and create reusable components and documentation for enterprise AI workflows.

Lead Responsible AI projects to detect, mitigate, and evaluate bias across GenAI, foundation models, and recommender systems. Collaborate with product and platform teams, deploy fairness interventions at scale, mentor junior engineers, and define technical strategy to align models with Pinterest policies and business metrics.

Lead and hands-on manage Seekr's AI infrastructure: design, build, and scale Kubernetes-based systems across cloud, on-prem, and edge; mentor engineers; automate operations; handle incidents and security; collaborate with software teams to ensure reliability, performance, and observability.

Lead technical design and execution for an AI/ML mission platform: drive architecture decisions, lead major engineering epics, simplify distributed systems, optimize edge and cloud performance, mentor engineers, integrate ML models and inference pipelines, and represent technical capabilities to DoD stakeholders.

Partner with Sales to lead technical discovery and scoping, design GenAI solution architectures, build bespoke demos and prototypes (RAG, fine-tuning, agents), author proposals and SOWs, capture reusable patterns into reference assets, and support handoffs to delivery teams. Requires up to 25% annual travel.

Senior technical leader responsible for architecting production-grade AI infrastructure for media & entertainment partners. Translate business needs into scalable GPU, storage, networking and inference solutions; validate ISV integrations; influence product roadmap; engage CTO-level stakeholders; and grow a team as the vertical scales.

Lead hardware-software co-design to enable AI/HPC and agentic AI stacks on RISC-V CPUs. Integrate and optimize low-level kernel infrastructure, runtimes, distributed execution, memory systems, and developer tools, collaborating with architects, compiler engineers, and kernel developers to meet performance targets.

Support embedded COOs across multiple clients by owning administrative and operational priorities, designing and documenting SOPs and AI-enabled workflows, managing project management systems and action items, coordinating hiring and ATS, handling executive scheduling, and preparing client-facing materials to ensure smooth operations and project momentum.

Lead Cobalt's AI and technology product roadmap, partner with engineering, data science, and creative teams to embed AI into agency work, and engage senior pharma clients in pitches and brand planning to drive adoption.

Lead Harbor's Data & AI consulting service line for law firms: own P&L and financial performance, develop and productize offerings, oversee delivery and talent development, drive business development and market thought leadership, and ensure measurable client value.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

Design, build, and deploy production-grade AI/ML and LLM-based systems. Lead end-to-end ML lifecycle, implement RAG and embedding pipelines, establish MLOps best practices, mentor engineers, and collaborate with cross-functional teams to deliver scalable, responsible AI solutions.

Design, build, and maintain AI-driven conversational agents and integrations for contact center workflows. Implement and tune NLP models, build transactional flows with backend systems, monitor production performance, and collaborate across architects, engineers, and product owners. Mentor junior engineers, contribute to CI/CD and observability, and continuously improve conversational AI solutions for customer-facing scenarios.

Designs and implements AI, automation, and analytics solutions for supply chain. Develops data models, governance, reporting, and advanced analytics; collaborates with process owners to enable data-driven decisions and trains/supports business users.

Lead deployment and scaling of AI/ML models, agentic tools, and automation across R&D. Drive MLOps, platform integration, compliance, stakeholder partnerships, capability building, end-user support, and metrics tracking to deliver measurable value.

Four-month full-time research fellowship supporting empirical AI safety projects using external models and APIs. Fellows receive mentorship, compute funding, and workspace access to produce public outputs (e.g., papers) across safety, robustness, interpretability, RL, and societal-impact topics.

Lead design and delivery of AI solutions (RAG and agentic architectures) for asset and wealth management clients. Architect retrieval pipelines, semantic models, GraphRAG, and cloud integrations. Manage project planning, governance, budgets, technical handover, and mentor development teams while promoting best practices and responsible AI.

Design and own end-to-end data quality systems for managed AI data studies: define rubrics, sampling plans, automated checks, launch gates, drift detection, dashboards, and calibration. Investigate integrity issues, run root-cause analysis, build automation in Python/SQL, and partner with Product, Engineering, and Operations to embed quality controls, train reviewers, and scale repeatable quality playbooks across programs.

Develop, analyze, and implement application systems using Python and generative AI frameworks. Build and maintain RESTful APIs, cloud-deployed containerized services, and ensure security, testing, and operational support. Consult with stakeholders, perform feasibility and post-implementation analysis, mentor junior analysts, and drive compliance with policies and risk controls.

Lead development of large-scale, multi-task robotic foundation models and manage the data flywheel: specification, collection, training, and real-world evaluation. Implement model specialization and fine-tuning, write production-quality Python for deep learning, and collaborate with robotics and hardware teams to deploy on real robots.

Lead research and implementation of large-scale, multi-task foundation models for dexterous robotic manipulation; manage the data flywheel from specification through collection, training, and real-world evaluation; fine-tune and specialize models; write maintainable Python deep-learning code; and collaborate with Robotics and Hardware teams to deploy models on real robots while co-leading AI engineering efforts.

Lead and grow the AI Forward Deployed Engineering team, oversee customer AI/ML transformations, and develop strategic partnerships while managing key accounts.

Design, build, deploy, and maintain production AI solutions and agents using Python or .NET on Azure. Implement RAG pipelines, semantic search and vector DBs, work with large-scale data (Databricks/SQL), evaluate model performance, and collaborate with engineers and analysts to productionize experiments.

Lead research and advisory on how emerging technologies (AI, quantum, blockchain, cloud-native, edge) reshape enterprise cybersecurity. Produce research, vendor analysis, frameworks, and client-facing presentations; advise CIOs/CISOs; mentor analysts; collaborate globally and drive research process improvements.