Staff/Senior Machine Learning Systems Engineer, Abridge

$200-265k

+Equity

Docker

Kubernetes

Python

Java

Tensorflow

Terraform

C++

PyTorch

Senior and Expert level

New York

San Francisco Bay Area

More information about location

2-3 days a week in office

Powering deeper understanding in healthcare through purpose-built AI

Job no longer available

Powering deeper understanding in healthcare through purpose-built AI

101-200 employees

HealthcareB2BArtificial IntelligenceEnterpriseMachine LearningSaaSMedTech

Job no longer available

$200-265k

+Equity

Docker

Kubernetes

Python

Java

Tensorflow

Terraform

C++

PyTorch

Senior and Expert level

New York

San Francisco Bay Area

More information about location

2-3 days a week in office

101-200 employees

HealthcareB2BArtificial IntelligenceEnterpriseMachine LearningSaaSMedTech

Company mission

To power a deeper understanding in healthcare.

Job

Company

Role

Who you are

5+ years of industry software development experience, with a background in design patterns, data structures, and test-driven development
Bachelor's Degree or greater in Computer Science/Engineering, Statistics, Mathematics, or equivalent
Proficient in developing production-quality software in languages such as C++, Python, or Java
Proficient with professional software engineering practices & standard practices for the full software life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
Experience with cloud based environments, Kubernetes or Docker, and Infrastructure as Code (Terraform, etc.)
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
Excellent interpersonal and written communication skills
Must be willing to work from our SF or NYC office 2-3x/week

Desirable

Experience in one or more relevant technical areas: natural language processing, machine learning, distributed systems, or building infrastructure for engineering/science users
Expertise in machine learning toolchains and techniques, such as Pytorch or Tensorflow
Demonstrated experience incubating and productionizing new technology, working closely with research scientists and technical teams from idea generation through implementation

What the job involves

From transcribing medical parts of the conversation to delivering key takeaways, our trailblazing work in machine learning research makes the Abridge experience possible. We're currently looking to add a machine learning engineer to our team to help us build and release more machine learning-powered value to our users
Architect, design, and implement high-quality machine learning software applications, infrastructure, and tools
Lead technical domains starting from the problem definition and technical requirements along with implementation and maintenance
Collaborate with machine learning researchers and engineers to implement and deploy algorithms, such as machine learning models
Work with stakeholders across machine learning and operations teams to iterate on systems design and implementation
Create re-usable software and systems to accelerate development
Profile, tune, and optimize system performance and debug production issues
Design systems for fault tolerance, scalability, security and continuous improvement

Our take

Summarising key elements of healthcare conversations is crucial for both physicians and patients. Medical scribes, though effective, are costly, and the healthcare system faces funding and staffing crises. This has created a demand for more efficient notetaking solutions.

This is where Abridge comes in; it has developed a HIPAA-compliant AI platform that transcribes, structures, summarises, and provides insights from audio or transcripts of medical conversations. It claims to work across all specialities and offers patient-friendly summaries in easy-to-understand language.

Abridge aims to alleviate pressure on the healthcare system from the patient's perspective, a unique approach among healthtech startups. While companies like Inovia, DOUB, and DeepScribe focus on assisting physicians with medical transcription AI, they lack Abridge's patient-centric features, which are valuable in enhancing the patient experience. Its unique focus, then, is part of the reason why it enjoyed two impressive rounds of funding in 2025 alone.

Freddie

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 6 rounds)

May 2025

$300m

SERIES E

Feb 2025

$250m

SERIES D

Total funding: $757.5m

Company benefits

Unlimited PTO, plus 12 national holidays
16 weeks paid parental leave, for all employees
Flexible working hours — we care more about what you accomplish than what specific hours you’re working
Remote work environment
Equity for all new employees
Generous equipment budget for your home office setup ($1600)
Opportunity to work and grow with talented individuals, and have ownership and impact at a high growth startup

Company HQ

SoMa, San Francisco, CA

Leadership

Shivdev Rao

(CEO)

Alongside their work as a practising Cardiologist at the University of Pittsburgh Medical Center, they also served as Physician Advisor in Residence and ultimately EVP at UPMC Enterprises; co-founded DocDok; and worked as a co-architect on a healthcare project at the Kauffman Foundation.

Sandeep Konam

(CTO)

Completed an MS in Robotics at Carnegie Mellon, then served as Senior Product Manager at UPMC Enterprises. Has delivered guest lectures at Carnegie Mellon, Stanford, and the University of Pittsburgh.

Salary benchmarks

We don't have enough data yet to provide salary benchmarks for this role.

Submit your salary to help other candidates with crowdsourced salary estimates.

Share this job

View 40 more jobs at Abridge