Requirements
AEP Hawaii is hiring a remote Senior Machine Learning Engineer to join our early-stage SaaS startup client.Â
This is a critical role focusing on building machine learning solutions for customer retention within a SaaS environment.Â
180-200K base salary + equityÂ
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