Job Description
Develop fit for purpose AIML models/algorithms/processes to address pharma/healthcare applications and innovative products upon completion of prototypes followed by the building of production grade algorithms/automation engines for client deliverables. Test for viability in order to deliver final products to clients. Able to bring newly researched ideas to reality quickly and on a large scale. Design, build, test, and deliver products from post-prototype to client delivery.
Essential Functions
- Guides the transformation of machine learning research domain expertise in the areas of human data into viable prototypes
- Guides the development of features of models on individual projects and/or products with guidance and support from others
- Develops understanding of the creation of new algorithms through working alongside other Machine Learning Engineers and Machine Learning Research Scientists
- Builds and trains new production grade algorithms that can learn from complex, high dimensionality data in order to uncover patterns from which machine learning models and applications can be developed
- Uses a variety of techniques in order to improve the performance of individual natural language processing and/or machine learning algorithms
- Guides the testing and validation of models to determine viability for deployment with guidance and support from others
- Guides the creation of fit for purpose experiments and prototype ideas to address pharma questions
- Consult for internal and external clients, implement solution development and innovation for complex proposals, conducts client AI project technical delivery
Qualifications
- Bachelor’s / Master’s Degree Master’s Degree in Machine Learning, Statistics, Computer Science, Physics, Math, or related field
- 2-3 years’ experience working on creating machine learning algorithms
- Programming experience using one or more of the following: Java, C++, Python, R, Go, Kubernetes, Deep learning or equivalent
- Experience working with large, real world datasets
