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Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.
Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.
We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the SoHo neighborhood of New York, the Mission District in San Francisco, and East Liberty in Pittsburgh.
AI Infrastructure Engineer
Abridge
Hybrid
San Francisco, CA, United States
Full-time
$179,000 -
$248,000
About Abridge
About the Role
As an AI Infrastructure 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.
Qualifications
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.
*Bonus Points If:
Expertise with model serving frameworks such as NVIDIA Triton Server, VLLM, TRT-LLM and so on.
Expertise with ML toolchains such as PyTorch, Tensorflow or distributed training and inference libraries.
Familiarity with GPU cluster management and CUDA optimization.
Knowledge of infrastructure as code (Terraform, Ansible) and GitOps practices.
Experience with container registries, image optimization, and multi-stage builds for ML workloads.
Experience orchestrating across ASR models or LLM models for building various GenAI applications.
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.
*Bonus Points If:
Expertise with model serving frameworks such as NVIDIA Triton Server, VLLM, TRT-LLM and so on.
Expertise with ML toolchains such as PyTorch, Tensorflow or distributed training and inference libraries.
Familiarity with GPU cluster management and CUDA optimization.
Knowledge of infrastructure as code (Terraform, Ansible) and GitOps practices.
Experience with container registries, image optimization, and multi-stage builds for ML workloads.
Experience orchestrating across ASR models or LLM models for building various GenAI applications.
Responsibilities
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.
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.
Benefits
Generous Time Off: 13 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employees.
Comprehensive Health Plans: Medical, Dental, and Vision plans for all full-time employees. Abridge covers 100% of the premium for you and 75% for dependents. If you choose a HSA-eligible plan, Abridge also makes monthly contributions to your HSA.
Paid Parental Leave: 16 weeks paid parental leave for all full-time employees.
401k and Matching: Contribution matching to help invest in your future.
Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits.
Learning and Development Budget: Yearly contributions for coaching, courses, workshops, conferences, and more.
Sabbatical Leave: 30 days of paid Sabbatical Leave after 5 years of employment.
Compensation and Equity: Competitive compensation and equity grants for full time employees.
... and much more!
Comprehensive Health Plans: Medical, Dental, and Vision plans for all full-time employees. Abridge covers 100% of the premium for you and 75% for dependents. If you choose a HSA-eligible plan, Abridge also makes monthly contributions to your HSA.
Paid Parental Leave: 16 weeks paid parental leave for all full-time employees.
401k and Matching: Contribution matching to help invest in your future.
Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits.
Learning and Development Budget: Yearly contributions for coaching, courses, workshops, conferences, and more.
Sabbatical Leave: 30 days of paid Sabbatical Leave after 5 years of employment.
Compensation and Equity: Competitive compensation and equity grants for full time employees.
... and much more!
