Machine Learning Engineer

Notable is the leading healthcare AI platform for transforming workforce productivity. Health systems, hospitals, and payers use Notable to improve healthcare quality, close gaps in patient care, drive member enrollment, and patient acquisition, retention, and reimbursement, scaling growth without hiring more staff.

We are on a mission to improve the lives of patients, staff, and clinicians - to improve healthcare for humanity. This isn't just a lofty goal - it's something we're achieving every single day. When you join Notable, you become part of a force actively transforming healthcare. Our aim to impact 100 million patients isn't just a number; it's a commitment to creating meaningful change on a massive scale.

Therefore, our culture is purposeful in pursuit of this mission. We believe our culture gives each person the opportunity to do the best work of their lives, work with the best teammates, and have fun achieving great things together.

Role Summary:

As an ML/AI engineer at Notable, you'll work on developing and deploying conversational AI models and agents across text, image and voice modalities, helping users automate tedious but valuable healthcare administrative tasks.

What You’ll Do:

• 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

What We’re Looking For:

• 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

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