The selected Engineer will work on a team of Machine Learning Natural Language Processing (NLP) Engineers responsible for building, developing and engineering state-of-the-art ML deployment patterns for ML platform to support multiple NLP and ML business solutions. These pipelines are used by organization to process healthcare claims and determine suitability and coverage. Candidates will spend 70% of their time developing and designing state-of-the-art NLP ML deployment patterns for ML platform to support multiple NLP and ML business solutions
Candidates should have an understanding of Data Science and ML Libraries, but this is an Engineering role.
Compensation:
$60/hr to $70/hr.
Exact compensation may vary based on several factors, including skills, experience, and education.
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.
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HR@insightglobal.com.
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- Bachelors Degree and 5 years of Natural Language Processing and Data Engineering experience
- Experience in designing state-of-the-art ML deployment patterns for ML platform to support multiple NLP and ML business solutions
- Senior to expert level experience writing Python code and maintaining large codebases
- Proficient in SQL and NoSQL databases like PostGreSQL and MongoDB and experience in querying languages.
- Experience in Data Science and ML Libraries specifically - numpy, pandas, scipy, scikit-learn, keras, tensorflow, Pytorch and langchain
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.