Lead Applied AI Scientist

Role overview Lead and grow an applied AI research and development team working on real-world problems with computer vision, audio processing, and language models. You’ll guide work from early proof of concept through production, balancing model quality with limits in hardware, compute, and available resources. The role spans the full path from raw signals and data to dashboards and insights, and includes collaboration with company leaders, product teams, colleagues, and sometimes clients.

Responsibilities - Set direction for applied AI projects and develop the team’s capabilities. - Test methods in computer vision, audio processing, and language models to address practical problems. - Move prototypes and demonstrations into production, accounting for algorithmic and resource efficiency. - Lead projects end to end, connecting data and model work to dashboards and actionable insights. - Analyze data and communicate technical findings to internal and external stakeholders. - Present results and technical approaches to clients in accessible terms when needed.

Requirements - Strong Python skills and familiarity with common machine learning libraries. - Either a particularly strong scientific background or a particularly strong computational background. - Experience solving problems in computer vision and audio processing. - Proficiency with Linux, Bash, SQL, and running code or models on physical machines. - Experience analyzing data and leading projects through to completion. - Clear communication skills and familiarity with AI development tools such as Claude or Codex.

Nice to have - Applied machine learning research experience. - Experience with Airflow or other data processing pipelines, software development lifecycles, cloud platforms such as AWS, or remote computer systems.

Benefits and work setup - Remote position for candidates in the US or Canada.