2024 Machine Learning Engineer Intern

Qualifications

• One semester or one year left and currently enrolled in a MS, or PhD program in Computer Science, Mathematics, Statistics, Engineering, Operations Research, or other quantitative field
• Strong programming skills in Python, an understanding of core computer science principles, and experience with Python data manipulation frameworks such as Pandas & PySpark
• Knowledge of SQL and relational database design
• Broad knowledge of basic computational statistics and good understanding of theoretical fundamentals of statistics
• Thorough and broad knowledge of machine learning modeling & training techniques, as well as best practices for ensuring robustness & performance
• Familiarity with practical data pipeline approaches such as ETL / ELT & stream processing
• Familiarity with technologies such as microservices, APIs, containerization (e.g., Docker, Kubernetes), and cloud environments (e.g., AWS)
• Strong interpersonal and verbal communication skills
• Ability to work effectively from your remote location using modern collaborative tools running on a company-provided MacBook Pro
• A modern productivity toolset to get work done : Slack, Miro, Loom, Lucid, Google Docs, Atlassian and more

Responsibilities

• You will be responsible for collaborating with cross functional partners and applying your data skills to deliver insights from data and build data-driven solutions for products, operations, marketing, and sales
• As a Machine Learning Engineer Intern, you will report to the Manager of Data Engineering
• Your role will span 10 to 12 weeks beginning in May 2024 and concluding in August 2024
• Collaborate with Data Engineers, Software Engineers, and other business partners to identify, gather, cleanse, and organize data sets needed for machine learning and AI models
• With guidance from seasoned Machine Learning Engineers & Data Scientists, write scalable code and build data pipelines to extract meaningful features from raw data
• Assist seasoned Data Scientists to design, train, and evaluate machine learning and / or AI models while adhering to best practices including model selection, validation, bias / variance tuning, performance assessment, sensitivity analysis, dimensionality reduction, etc
• Collaborate with seasoned Machine Learning Engineers & Data Scientists to design and implement machine learning and / or AI models as robust solutions that can be deployed into production at scale as microservices, reverse ETLs, or stream processing
• Collaborate with seasoned Machine Learning Engineers & Data Scientists to implement production monitoring metrics that detect performance degradations such as non-stationary behavior & anomalies, and that automatically trigger model retraining and / or alerts
• Work with stakeholders to identify model performance criteria and implement production solutions to monitor performance
• Follow our governance & development standards, including processes & frameworks for logging experiments, code & model quality standards, documentation, and source controlling artifacts
• Clearly document & present your work and informational materials at the appropriate level of detail to your team & business partners

Benefits

Competitive Salary

J-18808-Ljbffr