Abridge
Machine Learning Infrastructure Engineer
Part remote, part office, you need to live within commuting distance of a named location.
Hybrid · SF Office
Employer listed it 13 months ago · Added 4 days ago
Been open since 13 months ago. Long-running listings are sometimes left up after the role is filled.
Salary
$221,000–$260,000
Location
Hybrid · SF Office
Timezone
Not stated
Contract
Full-time
Experience
Mid
Category
Data
Published by the employer
Remote flexibility
Hybrid
This role is only partly remote, the employer expects time in the office around SF Office, Hybrid, so you need to live within commuting distance.
What the employer says
- Source listing states candidate location: "SF Office, Hybrid"
- Listing mentions "Hybrid"
What Nomaders makes of it
- Not suitable if you plan to move between countries
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
About Abridge
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 Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in 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'll 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.
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.
What You’ll Bring
5+ years of 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
Ideally, You Have
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
Requirements
- ·5+ years of 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
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, hybrid, matches where you plan to live and work.
- 2Tailor your CV to the role at Abridge, mentioning your remote working experience.
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 5d ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
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$221,000–$260,000 · You'll be taken to the employer's careers page.