Full-Time

Machine Learning Systems Engineer – Staff/Senior

Updated on 12/19/2024

Abridge

Abridge

51-200 employees

AI platform for clinical documentation automation

AI & Machine Learning
Healthcare

Compensation Overview

$200k - $265kAnnually

+ Equity

Senior

San Francisco, CA, USA

Must work from the SF office at least 3 times per week; relocation assistance available for candidates willing to move to San Francisco.

Category
Applied Machine Learning
AI & Machine Learning
Required Skills
Kubernetes
Python
Requirements
  • 5+ years of experience in ML model deployment and scaling, with a focus on production-quality software
  • Strong proficiency in Python and Kubernetes, with experience building scalable ML infrastructure
  • Expertise in designing fault-tolerant, highly available systems.
  • Experience working with cloud environments, Infrastructure as Code (IaC), and managing deployments using Kubernetes.
  • Proficiency in optimizing system performance, debugging production issues, and designing systems for scalability and security.
  • Experience in software design and architecture for highly available machine learning systems for use cases like inference, evaluation, and experimentation
  • Excellent understanding of low-level operating systems concepts, including multi-threading, memory management, networking and storage, performance, and scale
  • Bachelor's/Master’s Degree or greater in Computer Science/Engineering, Statistics, Mathematics, or equivalent
  • Excellent interpersonal and written communication skills
Responsibilities
  • Architect, design, and implement ML software systems for deploying and managing models at scale.
  • Stand up ML models for inference, starting with critical models like the 'linkages' model, and ensure they are capable of handling traffic increases.
  • Develop and maintain infrastructure that supports efficient ML operations, including model evaluations, deployments, and training at scale.
  • Collaborate closely with ML researchers, engineers, and cross-functional teams to ensure seamless integration of models with services like Zoom and Athena.
  • Work with stakeholders across machine learning and operations teams to iterate on systems design and implementation.
  • Optimize and maintain the performance of ML systems to ensure high availability, fault tolerance, and smooth scalability.
  • Troubleshoot production issues and continuously improve systems to enhance performance and efficiency.

Abridge provides a platform that changes how medical conversations are documented in healthcare settings. Its main product allows healthcare providers to record patient visits, which are then transformed into organized clinical documents. This helps doctors and other healthcare professionals save time on paperwork, allowing them to concentrate more on caring for their patients. Abridge stands out from its competitors by focusing specifically on improving the efficiency of clinical documentation through AI technology. The goal of Abridge is to enhance patient care and streamline the documentation process for healthcare providers, ultimately leading to better health outcomes.

Company Stage

Series C

Total Funding

$201.8M

Headquarters

Pittsburgh, Pennsylvania

Founded

2018

Growth & Insights
Headcount

6 month growth

55%

1 year growth

155%

2 year growth

388%
Simplify Jobs

Simplify's Take

What believers are saying

  • Partnerships with Corewell Health and Kaiser Permanente boost Abridge's market credibility.
  • Abridge's AI reduces clinician burnout, enhancing patient care and satisfaction.
  • The platform's focus on patient privacy aligns with industry trends, offering a competitive edge.

What critics are saying

  • Over-reliance on AI may decrease human oversight, risking documentation errors.
  • Rapid expansion could strain operational capacity, affecting service quality.
  • Integration challenges with EHR systems like Epic may disrupt service delivery.

What makes Abridge unique

  • Abridge offers AI-powered multilingual capabilities, enhancing communication in diverse healthcare settings.
  • The platform reduces cognitive load for clinicians, improving focus on patient care.
  • Abridge's integration with Epic streamlines workflows, reducing after-hours documentation time.

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