Applied AI Scientist

Role overview Explore and build applied machine learning solutions that help operators make decisions from data collected in both digital and physical environments. You’ll take projects from early experiments and demonstrations through production, balancing model quality and algorithmic efficiency while considering the full path from raw signals to user-facing insights. The position is remote within the US and Canada.

Responsibilities - Investigate approaches using computer vision, audio processing, and large language models to address practical problems. - Turn proof-of-concept and demo systems into production implementations suitable for resource-constrained environments. - Lead work end to end, from understanding input signals and data through to dashboards, analysis, and actionable outputs. - Develop solutions that account for hardware, compute, physical-world, and model limitations. - Explain technical work clearly to teammates and internal or external stakeholders.

Requirements - Strong Python skills and experience with common machine learning libraries. - Prior experience solving computer vision and audio-processing problems. - Comfort using Linux and Bash, including running code and models on physical machines. - Proficiency with SQL and working with data; experience analyzing data and drawing conclusions. - Clear communication skills and familiarity with AI development tools.

Nice to have - Applied machine learning research experience. - Familiarity with Airflow or other data-processing pipelines and with software development lifecycles. - Experience with AWS or another cloud platform, and with remote computer systems.