Machine Learning Scientist (Remote Allowed)
On-sitePittsburgh, Pennsylvania, United States
Job Summary
Research, develop, and deploy real-time machine learning-based AI tools for healthcare, focusing on patient monitoring and alerting solutions for maternal hemorrhage. Evaluate and iterate machine learning methodologies to solve novel problems in multimodal medical data analysis while collaborating on team projects. Deliver independent problem-solving on unstructured challenges using Python, PyTorch, and TensorFlow, with an emphasis on high-frequency signal and waveform data. Participate in long-term product development to identify intermediate milestones for cutting-edge clinical decision systems. This role supports NOMA AI's mission to revolutionize healthcare by proactively identifying risks of medical complications.
Required Qualifications
- Ph.D. degree in Computer science, Machine Learning, AI, or another equivalent field
- Relevant publications
- Ability to rapidly iterate and evaluate machine learning methodologies to solve novel problems
- Experience working with popular machine learning frameworks, including NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow
- Experience working with high-frequency signal and waveform data
- Experience with time-series data, high-frequency data, prediction modeling, and imbalanced data
- Expert Knowledge of Python
- Have experience in working and collaborating with others on team projects
- Ability to deliver with limited guidance, working on problems that are not structured
- 5+ years of programming experience
Desired Qualifications
- Experience with medical data, electronic health records, biosensor data, etc.
- Experience with real-time environments and model deployment
- Experience with major cloud environments and other distributed systems
- Interest and experience in software engineering (data pipelines)
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