Top AI & Machine Learning Jobs

Design, train, and deploy reinforcement learning agents that optimize power and compute resources across physical data centers. Develop multi-agent, model-based, and deep RL systems; build simulations; transition models into stable production deployments; improve strategies for peak shaving, workload shifting, and thermal management; and collaborate with platform engineers on APIs, telemetry, and infrastructure.

Leads the development and deployment of advanced analytics, AI, and machine learning solutions. Responsibilities include data preparation, pipeline development, predictive modeling, experimentation, model monitoring, generative AI applications, and production operationalization. Partners with business and technical teams, leads medium- to large-scale initiatives, mentors junior data scientists, communicates insights, promotes responsible AI, and delivers measurable business outcomes.

Build AI-powered workflows, features, integrations, and evaluations for insurance customers. Work across customer discovery, product, and engineering to solve operational problems, deploy solutions, investigate agent behavior, improve workflow reliability, and turn deployment patterns into reusable capabilities.

Embeds with strategic customers to design, build, and implement AI-driven solutions that scale support operations and drive measurable Fin adoption. Analyzes customer workflows and data, establishes measurement best practices, prototypes production-aware tools, and partners with Sales, Success, Product, and Engineering. The role also feeds deployment insights into product strategy and requires strong communication, adaptability, statistical analysis, SQL, Python, and experience with AI/ML evaluation or LLM applications.

Administer and improve enterprise AI platforms including Microsoft Copilot, Azure AI Foundry, ChatGPT Enterprise, and Claude Enterprise. Configure security, access, licensing, integrations, governance, monitoring, and cost controls. Investigate complex issues, perform root-cause analysis, develop technical standards and runbooks, manage platform initiatives, evaluate emerging technologies, and support responsible AI adoption. Collaborate with security, architecture, engineering, governance, and business teams while mentoring junior staff and providing platform guidance.

Build and scale production AI systems for Prophetic’s real estate intelligence platform. Responsibilities include developing agentic systems, data pipelines, inference workflows, evaluation benchmarks, geospatial processing, and machine learning applications across hundreds of millions of records. The role requires shipping reliable Python services, optimizing throughput and cost, integrating research into products, and collaborating with engineering and product teams.

Designs, builds, tests, and evolves enterprise AI agents, workflows, services, and applications. Owns technical decisions, architecture, scalability, security, responsible AI guardrails, and technical debt. Collaborates with product, UX, and engineering teams, conducts code reviews, communicates designs, and mentors junior engineers. Requires strong experience with production AI agents, LLMs, RAG, prompt engineering, orchestration frameworks, and software development, with preferred expertise in C#, .NET, Python, containers, cloud deployment, and scalable APIs.

Develop scalable C#/.NET enterprise applications powered by LLMs and RAG architectures. Responsibilities include integrating AI services, building REST APIs and backend services, working with vector databases and API gateways, implementing secure authentication, optimizing performance, and supporting CI/CD deployments. The role collaborates with cross-functional teams, participates in Agile ceremonies and code reviews, writes technical documentation, and supports production systems.

Build and operate Sysdig’s AI platform, including MCP servers, agent infrastructure, AWS Bedrock runtime and gateway, usage tracking, governance, observability, security controls, and employee AI automations. The role requires production ownership, AWS platform engineering, full-stack development, LLM application experience, and strong autonomy in designing secure, scalable AI systems.

Anthrogen is seeking exceptional talent for an open-ended, full-time onsite role in San Francisco. Candidates may propose research directions, technical capabilities, or unusual combinations of skills relevant to frontier AI and engineered biological systems. Applicants should demonstrate exceptional work, independent judgment, curiosity beyond a specialty, and a concrete record of building, discovering, or delivering meaningful results.