Staff Machine Learning Engineer

Phantom is a leading crypto wallet that helps tens of millions of users worldwide access decentralized finance, prediction markets, and tokenized assets. The company reached number one in Google Play's finance category and partners with major names like Hyperliquid, Stripe, Kalshi and Visa. With about 180 fully remote employees and backed by a $150M Series C from a16z, Sequoia Capital and Paradigm, Phantom is building infrastructure for the next generation of open financial systems.

The Engineering team is hiring a Staff Machine Learning Engineer to own the technical strategy and execution of growth and engagement ML systems. You'll design the architecture for ML pipelines that drive user acquisition, retention, lifetime value and product engagement, while mentoring senior engineers across the data organization.

Your day-to-day work will include

• Defining the long-term technical roadmap for growth and engagement ML, architecting production-grade systems for personalization, notification dispatch and user onboarding
• Designing and training sophisticated models for user lifecycle prediction: churn propensity, LTV forecasting, next-best-action recommendations and lookalike modeling
• Building recommendation engines and semantic search systems to surface relevant content and products to users
• Establishing experimentation frameworks using advanced A/B testing, causal inference and multi-variate testing to validate models in production
• Evaluating cutting-edge ML techniques including multi-armed bandits, reinforcement learning, LLMs for content generation and graph neural networks
• Partnering with Product and Growth Marketing to translate business hypotheses into machine learning problems
• Mentoring senior engineers and advocating for ML best practices around model monitoring, feature stores, reproducible pipelines and data governance

You bring 8+ years of professional machine learning or software engineering experience, with at least 3+ years at Staff, Principal or Tech Lead level. You have a proven track record building and scaling ML systems specifically for growth, marketing tech, recommendations or consumer engagement. Expert-level proficiency in Python, Scala or Java is required, along with hands-on experience in PyTorch, TensorFlow, JAX or XGBoost. You're deeply familiar with large-scale data infrastructure: Spark, Flink, Kafka, Snowflake, BigQuery, Ray, Kubeflow, MLflow or SageMaker. Strong understanding of causal inference, uplift modeling and statistical testing methodologies is essential. You connect algorithmic improvements directly to business metrics like MAU, DAU, conversion and retention, and you communicate complex technical concepts clearly to executives.

What we offer

• Competitive salary and equity package
• Comprehensive medical, dental and vision insurance at 100% coverage
• Remote work stipend for laptop, headphones and equipment
• Flexible hours with truly unlimited vacation time
• 401(k) retirement plan with wellness benefits
• Daily lunch benefit