Applied ML Engineer

Job Summary

Owning the research-to-production pipeline, the full-time Applied ML Engineer will streamline the transition of models from research to production, partnering with scientists to build robust workflows and optimize model performance in a remote environment.

Key responsibilities

• Own and manage the research-to-production pipeline, ensuring reliable deployment of models
• Collaborate with research scientists to translate experimental code into reproducible workflows
• Develop and enhance tooling for model training, evaluation, packaging, and deployment

Required qualifications

• Strong software engineering fundamentals with proficiency in Python and production-quality ML code
• Experience in taking ML models from research or prototype stage into production at scale
• Familiarity with modern deep learning frameworks, such as PyTorch
• Experience building ML pipelines and tooling for training orchestration and deployment
• Understanding of serving and inference optimization for production model workloads