What are the responsibilities and job description for the Machine Learning Engineer position at Tennr?
Company Description
Today, when you go to your doctor and get referred to a specialist (e.g., for sleep apnea), your doctor sends out a referral and tells you, “They’ll be in touch soon.” So you wait. And wait. Sometimes days, weeks, or even months. Why? Because too often specialists and medical services are overwhelmed with referrals and the painstakingly manual process it takes to qualify your referral prevents them from getting around to it on time, or sometimes at all. Tennr prevents these delays and denials by making sure every referral gets where it needs to go, with the right info, at the right time. Powered by RaeLM™ Tennr reads, extracts, and acts on every piece of patient information so providers can capture more referrals, slash denials, and reduce delays.
Role Description
We’re looking for a Machine Learning Engineer to help build the backbone of our healthcare process automation platform. You’ll wear many hats—researching and developing in-house models like RaeLM, designing information extraction pipelines, and building systems that transform messy, unstructured healthcare data into structured, actionable insights.
As an ML Engineer at Tennr, you’ll own end-to-end model development: architecting, training, deploying, and monitoring models—including open-source LLMs, vision-language models, and traditional computer vision systems—to deliver tangible value to our customers. You’ll also build and optimize data pipelines and ML infrastructure, ensuring our systems scale as data volume and complexity grow.
In this role, you’ll design and implement backend workflows that leverage ML to automate critical healthcare processes, fine-tune models for medical document understanding, and develop robust evaluation frameworks to measure and improve performance in complex, multi-model environments. Collaboration will be central—you’ll work closely with engineers, product, sales, and customer success teams to translate insights and feedback into actionable improvements and innovative solutions.
The ideal candidate is deeply curious, hands-on with both ML research and engineering, and has a proven track record of taking models from data to production at scale. This role is perfect for someone motivated to apply cutting-edge AI to real-world healthcare problems.
Responsibilities
Machine Learning Engineers at Tennr are expected to wear a variety of hats. In the role, you will be expected to do the following:
Today, when you go to your doctor and get referred to a specialist (e.g., for sleep apnea), your doctor sends out a referral and tells you, “They’ll be in touch soon.” So you wait. And wait. Sometimes days, weeks, or even months. Why? Because too often specialists and medical services are overwhelmed with referrals and the painstakingly manual process it takes to qualify your referral prevents them from getting around to it on time, or sometimes at all. Tennr prevents these delays and denials by making sure every referral gets where it needs to go, with the right info, at the right time. Powered by RaeLM™ Tennr reads, extracts, and acts on every piece of patient information so providers can capture more referrals, slash denials, and reduce delays.
Role Description
We’re looking for a Machine Learning Engineer to help build the backbone of our healthcare process automation platform. You’ll wear many hats—researching and developing in-house models like RaeLM, designing information extraction pipelines, and building systems that transform messy, unstructured healthcare data into structured, actionable insights.
As an ML Engineer at Tennr, you’ll own end-to-end model development: architecting, training, deploying, and monitoring models—including open-source LLMs, vision-language models, and traditional computer vision systems—to deliver tangible value to our customers. You’ll also build and optimize data pipelines and ML infrastructure, ensuring our systems scale as data volume and complexity grow.
In this role, you’ll design and implement backend workflows that leverage ML to automate critical healthcare processes, fine-tune models for medical document understanding, and develop robust evaluation frameworks to measure and improve performance in complex, multi-model environments. Collaboration will be central—you’ll work closely with engineers, product, sales, and customer success teams to translate insights and feedback into actionable improvements and innovative solutions.
The ideal candidate is deeply curious, hands-on with both ML research and engineering, and has a proven track record of taking models from data to production at scale. This role is perfect for someone motivated to apply cutting-edge AI to real-world healthcare problems.
Responsibilities
Machine Learning Engineers at Tennr are expected to wear a variety of hats. In the role, you will be expected to do the following:
- 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
- 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.
- Drive Impact: one of our company values is Cowboy, meaning you set the pace. You won’t just talk about things, you’ll get them done. And feel the impact.
- Develop Operational Expertise: learn the inner workings of scaling systems, tools, and infrastructure
- Innovate with Purpose: we’re not just doing this for fun (although we do have a lot of fun). At Tennr, you’ll join a high-caliber team maniacally focused on reducing patient delays across the U.S. healthcare system.
- Build Relationships: collaborate and connect with like-minded, driven individuals in our Chelsea office 4 days/week (preferred)
- Free lunch! Plus a pantry full of snacks.
- New, spacious Chelsea office
- Unlimited PTO
- 100% paid employee health benefit options
- Employer-funded 401(k) match
- Competitive parental leave
Salary : $200,000 - $240,000