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You will be updated with latest job alerts via emailUSD 175000 - 200000
1 Vacancy
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 dont 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 nations 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 a new standard for innovation in healthcare.
Role Summary:
As an ML/AI engineer at Notable youll 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 Youll 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 Were 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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Full-Time