Job details

AI Engineer

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About Tennr:

Today, when you go to your doctor and need to be referred to a specialist (e.g., for sleep apnea), your doctor sends a fax (yes, in 2024, 90% of provider-provider communication is a 1980s fax). These are often converted into 20+ page PDFs, with handwritten (doctor’s handwriting!) notes, in thousands of different formats. The problem is so complex that a person has to read it, type it up, and manually enter your information. Tennr built RaeLM™ (7B—trained on 3M+ documents) to read these docs, talk to your doc to ensure nothing is missed, and text you to help schedule your appointment so you can get better, faster.

Tennr is a NYC-based tech company that launched out of Y-Combinator and is backed by Lightspeed Venture Partners, Andreessen Horowitz, Foundation Capital, The New Normal Fund, and other top investors.

Key Responsibilities

As an AI Engineer at Tennr, you’ll bridge the gap between cutting-edge ML research and real-world product delivery. You’ll help build intelligent systems that use LLMs, vision models, and structured automation to solve hairy infrastructure, workflow, and UX challenges in U.S. healthcare.

Ship full-stack AI systems end-to-end
Build observability and debugging tools to capture model performance, user feedback, and long tail cases in production.
Go from ideation to code within hours; iterate quickly on experiments and data.
Work directly with ML, Sales, Customer Success, and Implementations to build AI systems for different use cases

Qualifications

Proficiency in full-stack development, with a strong understanding of web frameworks, backend systems, and cloud infrastructure
A track record of working through the full lifecycle of building, testing, deploying, scaling, and monitoring LLM-centered software architectures.
Understanding of how to test AI system performance beyond raw model accuracy.
Must articulate ideas well! A big part of making successful AI systems is telling people about them. This includes writing docs and technical reports at the minimum – and speaking in front of an audience at the extreme (optional).
Experience in healthcare or working with unstructured documents is a plus.

Average salary estimate

$105000 / YEARLY (est.)

min

max

$90000K

$120000K

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What You Should Know About AI Engineer, Tennr

At Tennr, we’re revolutionizing healthcare communication with our innovative AI solutions, and we’re looking for an enthusiastic AI Engineer to join our dynamic team in New York City. If you're passionate about leveraging cutting-edge machine learning technology to create real-world solutions, this is the perfect opportunity for you. As an AI Engineer, you will play a crucial role in bridging the gap between advanced ML research and actual product deployment. Imagine being the mastermind behind intelligent systems that not only use LLMs and vision models but also tackle complex workflow challenges in the U.S. healthcare landscape. You’ll get to ship full-stack AI systems from ideation to implementation quickly and efficiently. Collaborating closely with teams across ML, Sales, Customer Success, and Implementations, you'll develop AI systems that can adapt to various use cases. Your expertise in full-stack development and understanding of cloud infrastructure will be invaluable in building robust observability and debugging tools to monitor model performance. Plus, your ability to articulate technical concepts clearly will help us communicate our innovative solutions effectively. Join us at Tennr and make a difference in how healthcare information is processed and utilized, ultimately helping patients get the care they need faster and more efficiently.

Frequently Asked Questions (FAQs) for AI Engineer Role at Tennr

What are the primary responsibilities of an AI Engineer at Tennr?

As an AI Engineer at Tennr, you will be responsible for developing full-stack AI systems, bridging advanced ML research with practical product delivery. Your key tasks include creating observability and debugging tools, iterating on experiments quickly, and collaborating with multiple teams to build AI solutions tailored for healthcare cases.