Machine Learning Infrastructure Engineer, Abridge

• Strong experience in building and deploying machine learning models in production environments
• Deep understanding of container orchestration and distributed systems architecture
• Expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management
• Experience developing APIs and managing distributed systems for both batch and real-time workloads
• Excellent communication skills, with the ability to interface between research and product engineering

Desirable

• As a Senior/Staff Machine Learning Systems Engineer at Abridge, you’ll play a pivotal role in building and optimizing the core infrastructure that powers our machine learning models
• Your work will be instrumental in enhancing the scalability, efficiency, and performance of our AI-driven solutions. You will work with our Infrastructure and Research teams to build, deploy, optimize and orchestrate across our AI models
• Design, deploy and maintain scalable Kubernetes clusters for AI model inference and training
• Develop, optimize, and maintain ML model serving and training infrastructure, ensuring high-performance and low-latency
• Collaborate with ML and product teams to scale backend infrastructure for AI-driven products, focusing on model deployment, throughout optimization, and compute efficiency
• Optimize compute-heavy workflows and enhance GPU utilization for ML workloads
• Build a robust model API orchestration system
• Collaborate with leadership to define and implement strategies for scaling infrastructure as the company grows, ensuring long-term efficiency and performance