Responsibilities:
Develop and apply industry leading machine learning and deep learning systems to help solve business problems.
Apply natural processing and generative AI, and customize large models for use in product applications.
Develop and fine tune algorithms and models for time series and computer vision applications.
Lead design and coding of big data and machine learning systems.
Ability to translate business needs and goals into an AI approach and solution, and articulate findings to a non-technical audience.
Design model performance metrics and retraining schedule.
Assist with deploying models to public cloud infrastructure such as AWS and Microsoft Azure.
Mentor other engineers, remain aware of new developments in the field, and help build and grow the team.
Qualifications:
Bachelor's degree in computer science, mathematics, or a related field.
7 years of leading the design and architecture of new and existing machine learning systems.
5 years of experience in professional software development.
Experience with natural processing and generative AI.
Preferred Qualifications:
Graduate degree in computer science, mathematics, or another quantitative field.
10 years of experience in model development for time series data, signal, image, and video processing.
Deep knowledge of math, probability, statistics, and algorithms.
Outstanding analytical and problem-solving skills.
Prior experience in the healthcare or other regulated industries.
Experience using the following software/tools:
- Unsupervised and supervised learning methods.
- NLP and large model frameworks such as spaCy and langchain.
- Machine learning frameworks such as Keras, PyTorch, or Tensorflow.
- Libraries such as numpy, scikit-learn, scipy, and statsmodel.
- Programming: Python, .NET Core, Java.