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Phantom is a leading crypto wallet and trading platform with tens of millions of users globally, enabling access to perpetuals, prediction markets, tokenized assets, stablecoins, and other financial products. The company is fully remote, ~180 people, and backed by $150M Series C funding from a16z, Sequoia, and Paradigm.
You will serve as a Staff Machine Learning Engineer leading the technical strategy and execution of Growth and Engagement ML initiatives. This is a hands-on technical leadership role bridging advanced ML and business strategy, with responsibility for designing systems that drive user acquisition, retention, lifetime value (LTV), and product engagement.
Key responsibilities include:
**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 powering 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, LTV forecasting, next-best-action, lookalike modeling). Build and optimize recommendation engines and semantic search systems to surface relevant content, products, or features. Establish robust experimentation frameworks (advanced A/B testing, causal inference, multi-variate testing) to rigorously validate model variants in production.
**Collaboration & Mentorship:** Partner with Product and Growth marketing teams to translate business hypotheses into precise ML problems. Mentor and coach senior engineers across data and ML organizations, fostering technical excellence and continuous learning. Advocate for ML engineering best practices including model monitoring, feature store utilization, reproducible training pipelines, and data governance.
The company operates in a high-growth crypto/fintech market with strong user traction (millions acquired in 3+ years, consistent top-50 app ranking). Wallets are pivotal for crypto onboarding, the multi-chain world is expanding, and DeFi/NFTs are exploding—creating significant opportunity for impactful ML work.
**Requirements:**
- 8+ years professional experience in machine learning engineering, data science, or software engineering, with at least 3+ years in a Staff, Principal, or Tech Lead capacity
- Proven track record building and scaling ML systems specifically within growth, marketing tech, recommendation engines, or consumer engagement domains
- Extensive experience with large-scale data processing and distributed computing
- Expert-level proficiency in Python, Scala, or Java
- Strong experience with ML frameworks: PyTorch, TensorFlow, JAX, or XGBoost
- Hands-on experience with data & MLOps infrastructure: Spark, Flink, Kafka, Snowflake/BigQuery, Ray, Kubeflow, MLflow, or SageMaker
- Deep understanding of causal inference, uplift modeling, and robust statistical testing methodologies
- Business acumen to connect algorithmic improvements to top-line growth metrics (MAU/DAU, conversion rates, retention curves)
- Exceptional communication skills to explain complex technical architectures and algorithmic choices to non-technical stakeholders and executives
