Staff Machine Learning Engineer

Amit érdemes tudni

• Remote · Ismeretlen
• Távmunka-megjelölés további földrajzi adat nélkül — nem automatikus igen.
• Szint: Lead
• Fizetés: nem közölt

Helyszín és jogosultság

Távmunka-megjelölés további földrajzi adat nélkül — nem automatikus igen.

Remote · Remote

Megbízhatóság: 42%. A végső döntés a munkáltatóé – mindig olvasd el az eredeti hirdetést.

Pozíció

Phantom https://phantom.com is on a mission to connect the world to the freedom of open markets. Tens of millions of people all over the world use Phantom to access global markets that never close, including perpetuals, prediction markets, tokenized assets, stablecoins and memes. Phantom users are able to discover the markets that matter and the cultural moments that shape them, building conviction through real-time data and the verified performance of top traders. With self-custody and access to open networks at its core, Phantom lets them control their financial moves in the same app they use to safely store or spend money worldwide. Phantom has reached #1 in Google Play's finance category and consistently ranks in the top 50 apps across all categories. Phantom partners with many of the most trusted and influential names in finance like Hyperliquid, Stripe, Kalshi and Visa, to make the most popular and innovative financial products accessible to everyone. We are around 180 people, fully remote, backed by a $150M Series C investment from a16z, Sequoia Capital and Paradigm. ROLE OVERVIEW We are seeking a visionary and hands-on Staff Machine Learning Engineer to lead the technical strategy, architecture, and execution of our Growth and Engagement ML initiatives. In this role, you will bridge the gap between advanced machine learning and business strategy, designing systems that drive user acquisition, retention, lifetime value (LTV), and deep product engagement. As a technical pillar of the engineering organization, you will own the end-to-end lifecycle of complex ML models, mentor senior engineers, and collaborate closely with Product, Data Science, and Marketing leadership to move core business metrics. Key Responsibilities Technical Leadership & Strategy - Define the long-term technical roadmap for Growth and Engagement ML systems, ensuring scalability, reliability, and measurable business impact. - Architect and deploy production-grade ML pipelines and real-time decisioning systems that power personalization, notification dispatch, and onboarding flows. - Evaluate and integrate cutting-edge ML techniques, including multi-armed bandits, reinforcement learning, LLMs for content generation, and advanced graph neural networks. Execution & Modeling - Design, train, and validate sophisticated models targeting user lifecycle stages: propensity to churn, lifetime value (LTV) forecasting, next-best-action, and lookalike modeling. - Build and optimize recommendat

Rövidített kivonat. A teljes leírás és a jelentkezés a munkáltató oldalán érhető el.