Top AI & Machine Learning Jobs

The Senior AI Engineer will develop AI tools to enhance developer productivity at Datadog, focusing on LLM-based systems, prompts, and integration with existing products, while collaborating with various teams and users.

Lead design and delivery of AI-powered visualization and investigation features using LLMs. Build reliable, explainable systems combining deterministic product capabilities with generative models, drive prompt/context engineering, evaluation frameworks, and cross-team product-focused technical leadership and mentorship.

Lead GenAI/ML engineering projects within the APM team, focusing on model deployment, cross-team collaboration, and technical leadership.

Technical leader building AI-driven features for Datadog Notebooks: design, prototype, deploy, and scale ML workflows (agents, retrieval, prompt management), run experiments, define metrics, and coordinate cross-team product integration.

The Staff Applied Scientist will lead the evaluation strategy for AI agent integrations at Datadog, defining metrics and building datasets for quality improvements in agent performance through applied research and technical leadership.

The Distinguished Architect will provide technical leadership in AI, guide infrastructure discussions, and collaborate with stakeholders on AI observability solutions, requiring extensive experience and strategic thinking.

Lead a team in developing AI and ML models focusing on detection and text intelligence. Collaborate with product managers and support team development for impactful AI features.

As a Senior Applied Scientist, you will design machine learning solutions, develop scalable features, and analyze data within the Datadog app, collaborating with engineering and product teams.

As an AI Research Engineer, you will develop systems for research ideas, build datasets, implement models, and collaborate on AI capabilities with various teams.

Lead the design and development of Datadog's experimentation engine, translating complex statistical methods into production systems while collaborating with cross-functional teams and educating stakeholders on best practices.