Saxon Global
Machine Learning Engineer
Saxon Global, Clayton, Missouri, United States,
This is a 12 month contract with Centene Corporation. 100% remote. Visa - All but ho H1B. Must have LI.
Position Purpose: Perform tasks required to implement predictive modeling features as software, including building artificial intelligence (AI), machine learning (ML), and statistical models; packaging, deploying, integrating, and supporting AI/ML models; and building platforms and processes to facilitate the development of AI/ML models by others.
Education/Experience: Bachelor's degree in Computer Science, Data Science, Statistics, Math, Physics, or similar quantitative field or equivalent experience. 5+ years of related experience required. Software engineering proficiency in 2+ programming languages, databases, version control, statistics, or machine learning required. Preferred experience: SQL and noSQL databases, writing and consuming APIs, application containers (e.g. Docker), streaming data, building predictive models, compute clouds, creating database schemas, Linux administration, continuous integration/continuous deployment.
Responsibilities
Writes software code to enable and automate ML/AI model training and deployment Deploys predictive models using established software patterns Writes code to extract data from a variety of databases and data sources Writes reusable code libraries for use by other machine learning engineers Trains data scientists and machine learning engineers in best practices Builds ML/AI models using common methods within R and Python Investigates and adapts new software platforms for ML/AI and data engineering
Walk me through the day to day responsibilities of this the role and a description of the project:
Writes software code to enable and automate ML/AI model training and deployment Builds ML/AI models using common methods in Python Deploys predictive models using established software patterns Writes code to extract data from variety of databases and data sources Writes reusable code libraries for use by other machine learning engineers Trains data scientists and machine learning engineers in best practices Investigates and adapts new software platforms for ML/AI and data engineering Describe the performance expectations/metrics for this individual and their team:
Develop and test model hypotheses based on experimental results Architect and Develop ML solutions for stakeholders from design to deployment and integration Trains data scientists and machine learning engineers in best practices Reviews and provides constructive feedback of team members' code/merge requests Support models in production Actively participates in team discussions Tell me about what their first day looks like:
Meet team, get and verify accesses, set up system with help of team members. What previous job titles or background work will in this role?
Data Scientist, Machine Learning Engineer, Machine Learning Researcher, Artificial Intelligence Researcher, Artificial Intelligence Engineer,
Education Requirement:
Bachelor's
Education Preferred:
MS/PhD
Position Purpose: Perform tasks required to implement predictive modeling features as software, including building artificial intelligence (AI), machine learning (ML), and statistical models; packaging, deploying, integrating, and supporting AI/ML models; and building platforms and processes to facilitate the development of AI/ML models by others.
Education/Experience: Bachelor's degree in Computer Science, Data Science, Statistics, Math, Physics, or similar quantitative field or equivalent experience. 5+ years of related experience required. Software engineering proficiency in 2+ programming languages, databases, version control, statistics, or machine learning required. Preferred experience: SQL and noSQL databases, writing and consuming APIs, application containers (e.g. Docker), streaming data, building predictive models, compute clouds, creating database schemas, Linux administration, continuous integration/continuous deployment.
Responsibilities
Writes software code to enable and automate ML/AI model training and deployment Deploys predictive models using established software patterns Writes code to extract data from a variety of databases and data sources Writes reusable code libraries for use by other machine learning engineers Trains data scientists and machine learning engineers in best practices Builds ML/AI models using common methods within R and Python Investigates and adapts new software platforms for ML/AI and data engineering
Walk me through the day to day responsibilities of this the role and a description of the project:
Writes software code to enable and automate ML/AI model training and deployment Builds ML/AI models using common methods in Python Deploys predictive models using established software patterns Writes code to extract data from variety of databases and data sources Writes reusable code libraries for use by other machine learning engineers Trains data scientists and machine learning engineers in best practices Investigates and adapts new software platforms for ML/AI and data engineering Describe the performance expectations/metrics for this individual and their team:
Develop and test model hypotheses based on experimental results Architect and Develop ML solutions for stakeholders from design to deployment and integration Trains data scientists and machine learning engineers in best practices Reviews and provides constructive feedback of team members' code/merge requests Support models in production Actively participates in team discussions Tell me about what their first day looks like:
Meet team, get and verify accesses, set up system with help of team members. What previous job titles or background work will in this role?
Data Scientist, Machine Learning Engineer, Machine Learning Researcher, Artificial Intelligence Researcher, Artificial Intelligence Engineer,
Education Requirement:
Bachelor's
Education Preferred:
MS/PhD