Senior Machine Learning Systems Engineer, Abridge
$175-225k
+ Equity
More information about location
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
Job no longer available
$175-225k
+ Equity
More information about location
101-200 employees
Company mission
To power a deeper understanding in healthcare.
Role
Who you are
- Bachelor's Degree or greater in Computer Science/Engineering, Statistics, Mathematics, or equivalent
- 5+ years of industry software development experience, with a background in design patterns, data structures, and test-driven development
- 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
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 systems 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.
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