About Tennr
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.
About the Opportunity
As the first ML Ops Engineer at Tennr, you’ll play a crucial role in building and iterating on foundational Machine Learning and AI systems. You’ll own building machine learning training and inference pipelines that can handle increasing traffic demands and proliferation of product surface as we grow. You will be critical in ensuring our AI-driven healthcare platform is powered by robust, scalable, and efficiently deployed models.
Our Machine Learning team owns and develops multiple in-house, proprietary VLMs, LLMs, and other models that are purpose built for the ambitious problems we are solving in the healthcare space. This is not a role where you are repackaging and wrapping old innovations, but an opportunity to be on the cutting edge of experimentation and productization of net new capabilities. You’ll make impactful contributions and influence fundamental elements of our ML and data systems, expanding Tennr’s ability to rapidly iterate and solve critical problems for patients and providers.
Responsibilities
Architect, design, and implement ML software systems for deploying and managing models at scale.
Develop and maintain infrastructure that supports efficient ML operations, including data pipelines, model evaluations, deployments, and training at scale.
Collaborate closely with ML engineers, software engineers, and cross-functional teams to ensure seamless integration of models with data pipelines and products.
Troubleshoot production issues and continuously improve systems to enhance performance and efficiency.
Create tooling for online and offline evaluation of ML & LLM systems.
Candidate Qualifications
5+ years of experience in ML model deployment, infrastructure, and scaling in production environments
Strong software engineering fundamentals, with proficiency in Python and TypeScript
Experience in software design and architecture for highly available ML systems for use cases like inference, evaluation, and experimentation
Strong knowledge of observability, including logging, metrics, tracing, model performance monitoring, and alerting
Experience with distributed systems, reliability, and production incident response
Comfortable working in ambiguity with high ownership, moving quickly in a fast-paced startup environment, and proactively driving projects from idea to production
Nice to have:
Experience working with ML CI/CD and common ML frameworks like Pytorch, Tensorflow, etc.
Experience working with common inference frameworks like vLLM, TensorRT, Triton, etc
Experience with GPU orchestration, including managing GPU workloads/scheduling, cost management, cluster utilization, etc
Experience with GPU optimization (training/inference) involving CUDA profiling, memory optimization, multi-GPU communication, etc
Why Tennr?
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
Free lunch! Plus a pantry full of snacks.
Benefits
Chelsea office
Unlimited PTO
100% paid employee health benefit options
Employer-funded 401(k) match
Competitive parental leave