Top AI & Machine Learning Jobs

Design, build, and deploy LLM-powered applications, collaborating with Data Science teams to ensure agent systems operate reliably in production. Handle full lifecycle from prototype to production, integrating APIs and managing workflows.

Lead the design and deployment of machine learning models for personalized navigation and recommendations, managing projects end-to-end with a focus on user-centric solutions.

Design and deploy ML models for fraud detection, develop data pipelines, partner with teams to ensure effective fraud prevention, and enhance detection accuracy.

Lead design and implementation of AI and data transformation systems. Oversee end-to-end data pipelines, AI frameworks, and ensure responsible AI practices while mentoring teams and driving engineering standards.

Design and deploy AI systems to optimize semiconductor processes, leading initiatives and collaborating with engineering teams to improve workflows.

Oversee AI enablement efforts, lead teams to deliver enterprise AI solutions, integrate security, and translate business needs into technical strategies.

The Principal Engineer in Machine Learning will architect large-scale AI solutions, optimize training models, and collaborate on advanced AI/ML strategies in manufacturing.

The role involves deploying and supporting CrowdStrike's AI capabilities in cybersecurity, optimizing threat detection, and mentoring teams on AI solutions.

The role involves architecting AI applications, delivering scalable solutions, conducting research, and implementing high-quality code for cloud platforms. Requires collaboration and effective communication.

The VP of Agentic Systems will lead data science research and development, focusing on AI systems to enhance cybersecurity operations, requiring strong leadership and collaboration across technical teams.

This role involves building AI-powered applications, developing workflow automations, collaborating with teams, creating documentation, and continuous learning in AI and technology.

The Applied Scientist will focus on developing quantitative models, optimizing decision-making processes, and enhancing pricing strategies using advanced statistical methods and coding in Python.

The Applied Scientist will push the boundaries of applied AI, working on ML problems, developing models, and improving pricing systems.

Lead the architecture and implementation of a scalable AI/ML platform, focusing on data pipelines and integration of ML capabilities in business systems. Mentor and collaborate with cross-functional teams to optimize performance and deliver business value.

The co-op involves owning and delivering AI projects, conducting data analysis, building workflows, and communicating insights to stakeholders over a 6-month period.

As an AI & Analytics Intern, you'll work on data analytics, AI prompts, dashboard development, and solving business problems through data insights.

Design systems for AI agents to generate and manage code safely for non-engineers, focusing on security and distributed systems.

Lead product management in AI-driven safety solutions, focusing on video-based safety products, managing a roadmap and collaborating across teams for customer impact.