USAAI / Machine Learning Engineer II
2 нед. назад
300k USD / yearUSAMiddleOnsite
machine learning
Machine Learning Engineer role building AI systems as part of Gen's AI transformation.
Обязанности
- Our team is a core part of Gen’s AI transformation. We build machine learning systems that directly improve customer growth,
- retention, personalization, pricing, recommendations, billing success, and long-term customer value across a large global consumer
- portfolio.
- This role focuses on applied machine learning, experimentation, and business-impact modeling. You will build practical models that
- personalize customer decisions across in-app messages, email, portals, billing flows, and lifecycle journeys.
- We are looking for a hands-on AI / Machine Learning Engineer who can frame business problems, build models, design experiments,
- measure impact rigorously, and partner with engineering and product teams to bring models into production. Experience with
- recommender systems, uplift modeling, contextual bandits, pricing, or lifecycle personalization is a strong plus.
- • End-to-end ML ownership: Independently lead applied machine learning initiatives from data preparation and model development
- through experimentation, production deployment, monitoring, and continuous optimization.
- • Productionization and MLOps: Deploy and operate scalable ML solutions with robust workflows for batch or real-time inference,
- evaluation, monitoring, observability, versioning, retraining, rollback, and continuous model iteration.
- • Experimentation and impact measurement: Design and analyze A/B tests, holdouts, and validation frameworks to measure
- incremental customer and business outcomes.
- • Advanced model development: Design and build propensity, response, uplift, recommendation and ranking, contextual bandit,
- segmentation, optimization, and customer-value models.
- • Cross-functional delivery: Partner with ML infrastructure, data engineering, backend engineering, product, analytics, and business
- teams to integrate models into reliable production systems.
- • AI-first engineering workflows: Build agentic tools, automation, and reusable modules that streamline model development and MLOps
- workflows, improve productivity, and increase the speed, quality, and consistency of ML delivery.
Требования
- Education:
- Degree requirements are flexible. A technical degree in Computer Science, Data Science, Statistics, Mathematics, Operations
- Research, Economics, Engineering, or a related field is helpful, but equivalent practical experience is equally valued.
- A Master’s or PhD in a quantitative field is a plus, but not required.
- Experience:
- • Applied ML experience: Five or more years of professional experience in applied machine learning, data science, ML engineering,
- applied statistics, or a related field, or equivalent demonstrated impact.
- • Large-scale data: Experience building and evaluating models using large-scale behavioral, transactional, product, marketing, or
- customer data.
- • Experimentation: Experience designing experiments, defining success metrics, measuring incrementality, interpreting results, and
- translating findings into practical product or business decisions.
- Gen | AI / Machine Learning Engineer II
- • Production collaboration and ML operations: Experience partnering with engineering, product, analytics, and business teams to deploy
- and operate production ML systems, including inference pipelines, monitoring, observability, retraining, and cloud-based MLOps
- workflows.
- • Relevant specialization: Experience with personalization, recommendation, ranking, uplift modeling, causal inference, contextual
- bandits, pricing, optimization, or lifecycle decisioning is a strong plus.
- Skills:
- • Machine learning and modeling: Strong Python skills and hands-on experience with common ML frameworks, supervised learning,
- model selection, hyperparameter tuning, evaluation, and performance diagnosis.
- • Data processing and feature engineering: Strong SQL skills and experience with BigQuery, Spark, or similar platforms for data
- collection, cleaning, preprocessing, exploration, and feature development.
- • Analytics and experimentation: Strong statistical reasoning and practical knowledge of A/B testing, holdout design, causal
- measurement, incrementality, statistical significance, and business-impact analysis.
- • Production engineering and MLOps: Experience with cloud ML platforms, deployment pipelines, batch or real-time inference, CI/CD,
- model registries, monitoring, observability, retraining, rollback, and scalable system design.
- Personal Attributes:
- • Strong ownership: Takes responsibility for delivering high-quality solutions and measurable outcomes with limited oversight.
- • Business-impact orientation: Connects modeling and engineering decisions to customer experience, product performance, and
- business value.
- • AI-first builder mindset: Enjoys coding, modeling, automating, and shipping while proactively using AI and agentic tools to improve
- productivity and quality.
- • Clear, collaborative communication: Communicates assumptions, tradeoffs, risks, and results effectively across ML, engineering,
- product, analytics, and business teams.
Другое
- Gen is a global company dedicated to powering Digital Freedom through its trusted consumer brands including Norton, Avast,
- LifeLock, MoneyLion and more. Our combined heritage is rooted in financial empowerment and cyber safety for the first digital
- generations, and today we deliver award-winning cybersecurity, online privacy, identity protection and financial wellness solutions
- to nearly 500 million users in more than 150 countries.
- Together, we share a collective passion and vision to protect consumers and help them grow, manage and secure their digital and
- financial lives. We’re always looking for smart, fearless and high-impact talent who see AI as a teammate – leveraging it to move
- faster and deliver meaningful results.
- When you’re part of Gen, you’ll have the flexibility, tools and support to do your best work and grow your career – from flexible
- working options and time off to competitive pay, benefits and well-being programs.
- At Gen, we are scrappy and relentlessly customer driven. We create room for healthy debate, experimentation and continuous
- learning, and we seek out people with different experiences, identities and ideas to join our team. You’ll work with people who back
- each other, respect each other and understand that our differences are a competitive advantage.
- If this sounds like you, we’d love you to be part of Gen.
- Our hiring process includes the following steps:
- 1. Video Introduction: Submit a brief video introducing yourself, your work, and your most relevant experience.
- 2. Technical interview: Demonstrate your applied machine learning, analytical, and engineering capabilities.
- 3. Hiring manager interview: Meet with the hiring manager to discuss your background and fit for the role.
- 4. Final interview: Meet with our AI leadership, including the Chief AI Officer, for a final assessment.