Embedded Research Scientist (AI)

TL;DR

Embedded Research Scientist (AI): Advance frontier AI research in post-training, reinforcement learning, agentic modeling, and specialized architectures while embedded with customers in critical industries. Focus on designing research strategies, prototyping training pipelines, conducting evaluations, and transitioning breakthroughs into production systems via Mosaic platform.

Location: New York City

Company

Transforming critical institutions like healthcare, manufacturing, and energy with applied AI through forward-deployed expertise, in-house Mosaic toolkit, and partnerships with Anthropic, McKinsey, AWS, and General Catalyst.

What you will do

• Identify high-impact research problems at the intersection of frontier AI and customer business needs.
• Design and execute strategies across LLM post-training, RL, agentic modeling, and specialized development.
• Prototype and scale training pipelines, experiment with architectures and optimization techniques based on feedback.
• Conduct large-scale customer-facing evaluations to demonstrate business value and drive production adoption.
• Translate business problems into research questions and outcomes into actionable insights for stakeholders.
• Partner with Applied AI Engineers to deploy research into Mosaic platform features.
• Build relationships with customer teams and contribute to distributed training infrastructure.

Requirements

• MS/PhD in Computer Science, ML, or related field, or equivalent experience.
• Depth in LLM and ML fundamentals.
• Experience implementing and debugging large-scale ML systems.
• Can work directly with customers: translate business problems into research, communicate technical concepts to non-technical stakeholders, iterate on feedback.
• Proven track record of execution and passion for deploying research in production for industries like healthcare, supply chains, energy, finance.
• Excellent communicator with technical and non-technical audiences, extreme ownership.

Culture & Benefits

• Dream bigger: Tackle ambitious problems with optimism and responsibility.
• Heart in the game: Care deeply about impactful work without monitoring hours.
• Win for the customer: Focus on outcomes and delivery as strategy.
• Make the call: High-agency decisions with high-bandwidth communication, no silos.
• Intensity with kindness: Excellence, candor, prioritization, urgency balanced with trust and vulnerability.