ML Operations, Full Stack (New Grad) at Abridge

San Francisco, California, United States

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$155,000 – $165,000Compensation

Entry Level & New GradExperience Level

Full TimeJob Type

UnknownVisa

Healthcare, AIIndustries

Requirements

Currently pursuing a Bachelor's or Master’s degree in Computer Science, Software Engineering, Machine Learning, or a related technical field
Expected graduation date in Spring 2026
Expertise with ML toolchains such as PyTorch, Tensorflow or distributed training and inference libraries
Experience in building and deploying machine learning models in production environments
At least one prior software engineering internship or co-op experience
Passion for and understanding of Abridge’s mission
A curious, adaptable, and proactive mindset, with a desire to learn and grow in a fast-paced startup environment
A willingness to pitch in wherever needed—we move fast, and we need team players who are eager to contribute
Must be willing to work from our San Francisco or New York City office at least 3x per week

Responsibilities

Collaborate with ML and product teams to scale backend infrastructure for AI-driven products, focusing on model deployment, throughput optimization, and compute efficiency
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 across our cross-functional product teams, working closely with design, product, and infrastructure to ship features to our customers

Skills

Key technologies and capabilities for this role

Machine LearningKubernetesML EngineeringModel DeploymentInfrastructureBackendAI ModelsCompute OptimizationModel ServingModel Training

Questions & Answers

Common questions about this position

What is the salary range for this ML Operations role?

The salary range is $155K - $165K.

Is this position remote or hybrid?

The position is hybrid.

What skills and experience are required for this role?

Candidates need to be pursuing a Bachelor's or Master’s in Computer Science, ML, or related fields with Spring 2026 graduation, expertise in ML toolchains like PyTorch or TensorFlow, experience deploying ML models in production, and at least one software engineering internship.

What is the team structure and work environment like at Abridge?

You'll join the ML Engineering team, working with Infrastructure and Research teams, collaborating across cross-functional product teams including design, product, and infrastructure, and receiving mentorship from experienced engineers in a fast-paced startup with pods.

What makes a strong candidate for this new grad position?

Strong candidates have the required degree and graduation timeline, ML toolchain expertise, production ML deployment experience, prior internship, passion for Abridge’s mission, and a curious, adaptable, proactive team-player mindset in a fast-paced environment.

Abridge

AI platform for clinical documentation automation

About Abridge

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 the needs of healthcare providers, payers, and pharmaceutical companies, offering a solution that improves both documentation efficiency and patient outcomes. The goal of Abridge is to enhance the quality of patient care while making the documentation process easier for healthcare professionals.

Pittsburgh, PennsylvaniaHeadquarters

2018Year Founded

$201.8MTotal Funding

SERIES_CCompany Stage

AI & Machine Learning, HealthcareIndustries

51-200Employees

Benefits

Medical insurance

Dental Insurance

Vision Insurance

Unlimited Paid Time Off

Equity

Flexible Spending (FSA) & Health Savings (HSA) Accounts

Learning and Development budget

401k Plan

Paid Parental Leave

Flexible working hours

Home Office Budget

Sabbatical Leave

Risks

Rapid expansion may strain Abridge's resources and affect service quality.

Integration challenges with EHR systems could disrupt workflows and data consistency.

Data privacy concerns in AI applications may lead to regulatory scrutiny.

Differentiation

Abridge transforms medical conversations into actionable clinical documentation using AI.

The platform supports over 28 languages and 50+ medical specialties.

Abridge's integration with EMR systems enhances clinician efficiency and patient care.

Upsides

Abridge's partnership with Mayo Clinic expands its reach to over 1 million patients.

The $150 million Series C funding accelerates AI technology development and integration.

Abridge's multilingual capabilities improve communication in diverse patient populations.

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