Member of Technical Staff, Machine Learning Infrastructure
at Abridge
SF Office, remote, full time, USD 2,21,000–2,60,000 / year, 5+ years
posted 25 Aug 2025
- NVIDIA Triton Server
- Tensorflow
- ASR
- GenAI
- GitOps
- LLM
- CUDA
- PyTorch
- Terraform
- Ansible
- TRT-LLM
- Kubernetes
- VLLM
About the role
Remote: yes Posted: 2025-08-25
ABOUT ABRIDGE
Founded in 2018, Abridge is the first AI-native clinician intelligence platform organized around the patient, built for clinicians, and designed to help health systems coordinate the clinical, financial, and evidence-based decisions for every moment of care. Powered by purpose-built AI for healthcare, Abridge connects patients, providers, payers, and life sciences companies. This year, the platform will support more than 100 million patient-clinician conversations across more than 300 of the largest and most complex health systems in the U.S. With deep workflow integration, the Abridge clinician intelligence platform has been validated to support encounters in 28+ languages across specialties and care settings.
Abridge is setting the industry standard for the responsible deployment of Al across health systems with continual and transparent Al evaluation. Clinical decision support references and cites gold-standard sources of evidence, and features like Linked Evidence map AI-generated documentation to source data, helping clinicians quickly trust and verify the output.
Abridge was awarded Best in KLAS for Ambient AI in 2025 and 2026, in addition to other accolades, including TIME Best Inventions of 2024 and 2025, CNBC Disruptor 2025, and Fast Company’s Most Innovative Companies 2025.
We are a growing team of practicing clinicians, AI scientists, PhDs, creatives, technologists, and engineers working together to transform healthcare. We have offices located in San Francisco, New York, and Pittsburgh.
THE ROLE
As an ML Infrastructure Engineer at Abridge, you’ll play a pivotal role in building and optimizing the core inference 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.
What you would do
- Design, deploy and maintain scalable Kubernetes clusters for AI model inference and training
- Develop, optimize, and maintain ML model serving 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, throughput optimization, and compute efficiency.
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