Machine Learning Engineer, Tennr
$200-240k
+ Equity
Automation platform for healthcare operations
Open for applications
Automation platform for healthcare operations
201-500 employees
Open for applications
$200-240k
+ Equity
201-500 employees
Company mission
To ease the administrative burdens on healthcare providers.
Role
Who you are
- 3+ years of experience (post BS/MS) in an ML research/engineering role
- Proven track record of building and maintaining scalable web applications, particularly in high-volume workflow automation and data processing
- Experience integrating machine learning models into production environments
- Can efficiently translate open-ended problems into actionable solutions
- Familiarity implementing novel NLP research ideas and techniques. Prior publications in top conference journals is a plus
- Prior experience in a startup environment is a plus
What the job involves
- Machine Learning Engineers at Tennr are expected to wear a variety of hats
- End-to-end product development: architect, train, deploy, and monitor models that drive direct customer value across our product
- Data processing and ML Ops: optimize scalable data processing pipelines in our platform and maintain machine learning infrastructure
- Backend integration: design and maintain complex workflows that leverage machine learning to drive automation
- Product evaluation: Collaborate with sales and customer success teams to respond to feedback from our customers and prospects
- Custom models: Fine-tune LLMs and VLMs for medical document understanding tasks
- Evaluation Criteria:
- Technical Proficiency: Your skill in full-stack development and contribution to our tech stack
- Project Execution: Efficiency and quality in delivering projects within set timelines
- Innovation and Contribution: Your ability to enhance our system with new ideas and improvements
- Collaboration and Communication: Effectiveness in team collaboration and clarity in communication
- Adaptability and Learning: Willingness to embrace new technologies and a commitment to continuous learning
Our take
In the healthcare system, there are inefficiencies associated with the referral process to specialists. Often coming in various forms, from email to fax, without any standardized structure, this leads to administrative burdens and significant delays in patient care.
Tennr has developed a machine learning and document scanning platform that automates the extraction of relevant information from referrals and facilitates faster appointment scheduling. With its focus solely on the healthcare industry, it addresses the complexities of medical terminology and ensures doctors, clinics and insurers stay informed throughout the process.
It's had a successful start, customers reporting significant improvements in their workflows, signalling strong market demand for the solution. This success is accompanied by strong funding, enabling the company to focus on accelerating its growth. It has also announced the launch of Tennr Network, which provides real-time updates to referring and receiving providers, as well as patients, on the status of any referral.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 5 rounds)
Jun 2025
$101m
SERIES C
Oct 2024
$37m
SERIES B
Total funding: $156.3m
Company benefits
- Meaningful equity
- In-person culture
- Promoting from within
- 401k matching
- Unlimited PTO
- Free lunch (and a pantry stocked with a strangely wide array of puffed corn snacks)
Company HQ
Chelsea, New York, NY
Leadership
Trey Holterman
(Co-Founder & CEO)They studied Computer Science with a focus on Machine Learning at Stanford. Prior to starting Tennr, they focused on applying their research in the health technology world at HealthIQ and Strava.
Diego Baugh
(Co-Founder & CPO)They studied Computer Science at Stanford with a focus on Human Computer Interaction and Design. Prior to Tennr, they built automation systems at Goldman Sachs as an Automation Engineer.
Tyler Johnson
(Co-Founder & CTO)They studied Computer Science with a focus on Systems and Networking at Stanford. Prior to Tennr, they worked as a Lead Engineer at Tanduo, where they built bespoke data workflows for large industrial companies.
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 27 more jobs at Tennr