Overview

Notable is the leading intelligent automation company for healthcare. Customers use Notable to drive patient acquisition, retention, and reimbursement, scaling growth without hiring more staff. We don’t just make software. We are on a mission to fix the broken U.S. healthcare system by helping to eliminate the massive administrative burden that is placed on our nation’s healthcare staff. We hire people from diverse backgrounds and are always looking for employees who bring fresh ideas to our space. Passion is paramount, and at Notable, you will get to work with other talented people who aim to set the new standard for innovation in healthcare.

As an ML/AI engineer at Notable, you’ll work on developing and deploying machine learning models which provide the intelligence powering robotic processes that underpin critical healthcare workflow automation. The types of AI tasks range from natural language understanding, including document entity extraction, reading comprehension, to computer vision for robotic process automation, such as object detection and optical character recognition. You’ll work closely with the product development team to define ML systems tailored to our needs, help us build the necessary data and computing infrastructure, and ship new solutions to enable intelligent automation.

We look for smart people who can implement well crafted solutions to complex problems in a fast paced environment, and who can help us attract more smart people.  We don't expect you to have experience with our stack (Google Cloud Platform, Python, Tensorflow, Kubeflow, PyTorch, FastAPI, Kubernetes), but we do look for demonstrated mastery of your chosen development stack and a desire to learn new technologies.

Our interview process is meant to be representative of the kinds of work we will do together day-to-day and week-to-week. You’ll start with an intro call to learn more about Notable and the team, followed by a remote two-hour take-home exercise where you will be asked to work on a problem similar to ones we work on a daily basis and then email it back, then either an in-person onsite with multiple one-on-one sessions and lunch with the team or a virtual alternative.

Day-to-day responsibilities:

• Work with the product development team and product managers to define scope of work, timeline and product specifications

• Work with backend engineers to deploy, maintain and scale AI models

• Define interfaces between the microservices that runs and delivers AI models

• Discover, collect, clean and transfer data to train AI models

• Experimentation of different AI models, methodologies, frameworks and communicate critical evaluation metrics to product teams.

• Explore, refine, improve best practices within the ML team

• Push the boundaries of ML and AI and innovate on how to best leverage existing technologies to solve new problems

Experience: 

• 7+ years of experience working in a relevant role

• Demonstrated ability to translate business requirements and metrics into machine learning model specifications

• Quickly prototype new models from open-sourced code and demonstrate results

• Ability to design and train new model architectures for complex data

• Experience working with real-world data: large, messy, incomplete, irregular, etc.

• Experience working with a mix of structured and unstructured data

• Proficiency with Python and the standard ML stack (numpy, pandas, scikit-learn)

• Experience with a deep learning package, e.g. Tensorflow, PyTorch

• Experience deploying ML models in production

Beware of job scam fraudsters! Our recruiters use @notablehealth.com email addresses exclusively. We do not conduct interviews via text or instant message and we do not ask candidates to download software other than Zoom, to purchase equipment through us, or to provide sensitive personally identifiable information such as bank account or social security numbers. If you have been contacted by someone claiming to be me from a different domain about a job offer, please report it as potential job fraud to law enforcement and contact us here.