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Senior Machine Learning Engineer

Hawaii Remote

Job Type :

Full-time

180-200K + equity

Requirements

AEP Hawaii is hiring a remote Senior Machine Learning Engineer to join our early-stage SaaS startup client. 


This is a critical role focusing on building machine learning solutions for customer retention within a SaaS environment. 


180-200K base salary + equity 


Required Experience

  • 7+ years of professional experience developing production ML systems, including model deployment, monitoring, and maintenance in production environments.

  • Strong background in statistical analysis and mathematical modeling

  • Advanced proficiency in R, including expertise with packages such as data.table, glmnet, xgboost, randomForest, ggplot, and other advanced data manipulation and modeling libraries.

  • Experience with Python ML ecosystem (pandas, NumPy, SciPy, scikit-learn).

  • Deep understanding of, and experience with software engineering best practices (version control, CI/CD, testing)

  • Proficiency with cloud platforms (AWS, GCP)


Responsibilities

  • Architect, develop, and optimize advanced machine learning solutions within our framework

  • Lead the unification of disparate ML components into a cohesive ecosystem

  • Design and implement scalable ML pipelines that meet production requirements

  • Develop sophisticated statistical models using R for data analysis and predictive modeling

  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions


Education

  • Ph.D. in Computer Science, Statistics, Applied Mathematics, or related field required

  • Exceptional candidates with a Master's degree and outstanding experience will be considered


Preferred Qualifications

  • Contributions to R packages or the R ecosystem

  • Experience with systems integration and API design

  • History of technical leadership in previous roles


Intangibles

  • Driven to deliver results; mature understanding of tradeoffs necessary to meet deadlines.

  • Exceptional problem-solving abilities and attention to detail.

  • Excellent written and verbal communication skills, with the ability to explain complex concepts to technical and non-technical stakeholders

  • Self-motivated with the discipline to work effectively in a remote environment

  • Comfort with ambiguity; ability to make decisions with incomplete information

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