Machine Learning Engineer I
$176,000–$191,000 year
RemoteUnited States
Job Summary
Own well-defined machine learning projects from data exploration and model development through validation, deployment, and iteration. Build predictive, recommendation, and uplift models for customer personalization while preparing datasets and defining modeling targets. Design A/B tests and holdouts to measure model performance and business impact, then collaborate with engineering and product partners to integrate solutions into production. Use AI coding assistants and automation to streamline workflows, ensuring data quality and feature consistency. This role sits within Gen's core AI transformation team, focusing on improving customer growth, retention, and long-term value across Norton, Avast, and MoneyLion.
Required Qualifications
- Two or more years of professional experience in applied machine learning, data science, ML engineering, applied statistics, or a related field
- Experience building and evaluating models with real-world data
- Experience analyzing behavioral, transactional, product, marketing, or customer data
- Experience translating findings into practical insights or recommendations
- Experience defining success metrics, analyzing experiments, evaluating model performance, and interpreting business impact
- Experience working with engineering, product, analytics, or business partners to deploy or apply data-driven solutions
- Strong Python skills
- Practical knowledge of supervised learning
- Knowledge of model selection
- Knowledge of hyperparameter tuning
- Knowledge of evaluation
- Knowledge of performance analysis
- Strong SQL skills
- Experience using platforms such as BigQuery, Spark, or similar tools for data extraction, cleaning, preprocessing, exploration, and feature development
- Strong analytical and statistical reasoning
- Experience with A/B testing
- Experience with holdout design
- Knowledge of statistical significance
- Knowledge of business-impact measurement
- Familiarity with common ML libraries
- Familiarity with cloud data or ML platforms
- Familiarity with version control
- Familiarity with AI-assisted development tools
- Takes responsibility for assigned work
- Follows through on commitments
- Proactively addresses issues
- Connects modeling and analysis to customer experience and measurable outcomes
- Enjoys modeling, analyzing, automating, and shipping while using AI tools to improve productivity and quality
- Learns quickly
- Seeks feedback
- Continuously develops technical and business knowledge
- Communicates ideas, assumptions, results, and challenges effectively with technical and non-technical partners
Desired Qualifications
- A technical degree in Computer Science, Data Science, Statistics, Mathematics, Operations Research, Economics, Engineering, or a related field
- Equivalent practical experience to a technical degree
- A Master's or PhD in a quantitative field
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