О компании
Phantom connects people to open global markets, including perpetuals, prediction markets, tokenized assets, stablecoins, and memes. Its app provides access to real-time market data and verified trader performance, with self-custody and open networks at its core. Phantom also partners with companies in finance to make financial products accessible to everyone.
Задачи
•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 for personalization, notification dispatch, and onboarding flows
•Evaluate and integrate machine learning techniques, including multi-armed bandits, reinforcement learning, LLMs for content generation, and graph neural networks
•Design, train, and validate models for churn propensity, lifetime value forecasting, next-best-action, and lookalike modeling
•Build and optimize recommendation engines and semantic search systems to surface relevant content, products, or features
•Establish experimentation frameworks, including advanced A/B testing, causal inference, and multivariate testing, to validate model variants in production
•Partner with Product and Growth Marketing teams to translate business hypotheses into actionable machine learning problems
•Mentor and coach senior engineers across data and ML organizations
•Advocate for ML engineering best practices, including model monitoring, feature store utilization, reproducible training pipelines, and data governance
Требования
•8+ years of professional experience in machine learning engineering, data science, or software engineering
•At least 3+ years in a Staff, Principal, or Tech Lead capacity
•Proven experience building and scaling ML systems in growth, marketing tech, recommendation engines, or consumer engagement
•Extensive experience with large-scale data processing and distributed computing
•Expert-level Python, Scala, or Java
•Experience with PyTorch, TensorFlow, JAX, or XGBoost
•Experience with Spark, Flink, Kafka, Snowflake/BigQuery, Ray, Kubeflow, MLflow, or SageMaker
•Deep understanding of causal inference, uplift modeling, and statistical testing methodologies
•Ability to connect algorithmic improvements to business growth metrics, including MAU/DAU, conversion rates, and retention curves
•Ability to explain complex technical architectures and algorithmic choices to non-technical stakeholders and executives
Будет плюсом
No additional preferred qualifications specified
Условия
•Competitive salary and equity
•Medical, dental, and vision insurance fully covered
•Stipend for a remote/WFH setup, including a laptop, headphones, and other work gear
•Flexible hours
•Unlimited vacation
•401(K) retirement plan
•Wellness benefit
•Daily lunch benefit
