Machine Learning Engineer

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