Top AI & Machine Learning Jobs

Design, build, and productionize machine learning models and data pipelines for recommendation, bidding, and forecasting. Collaborate with product and engineering teams, evaluate and monitor model performance, maintain high-quality tested code, prototype research ideas, and run experiments. Hybrid schedule: four days in-office, one remote.

The Data Scientist will analyze data to provide insights, partner with teams for metrics, develop models, and create accessible visualizations to influence product and program strategies.

As a Machine Learning Subject Matter Expert, analyze, validate, and improve ML systems, mentor teams, and drive product innovation within a collaborative environment.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

Lead applied research and engineering for feedback-driven agentic AI: define reward modeling and reinforcement learning roadmap, design production learning loops and evaluation frameworks, run large-scale experiments, and ship research into production while partnering across product and engineering.

Partner with Digital Assets, Finance, Treasury, and Risk to design measurement frameworks, perform strategic analysis and modeling, build scalable SQL-driven automation and dashboards, analyze on-chain and finance data, create visualizations, and drive data-informed product decisions for USDC and related digital asset offerings.

As the Director of Data Science, you'll mentor teams, oversee projects, drive data-driven decisions, and implement AI and ML solutions while enhancing our data pipeline.

Lead evaluation and enterprise adoption of emerging technologies (e.g., generative and agentic AI). Define reference architectures, standards, governance, and roadmaps; resolve cross-program architecture issues; guide risk/benefit analysis and educate IT and business leaders to ensure secure, scalable, enterprise-aligned adoption.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

Design, prototype, and deploy LLM-powered agents, RAG workflows, and automations that accelerate internal teams and customer-facing product features. Integrate AI systems with SaaS tools, build reusable components and evaluation frameworks, embed with business teams to deliver measurable outcomes, and establish standards for responsible AI, monitoring, and cost control across the company.