7 hours ago
Responsibilities
- Define the long-term technical roadmap for growth and engagement machine learning systems.
- Architect and deploy production-grade ML pipelines and real-time decisioning systems for personalization, notification dispatch, and onboarding.
- Evaluate and integrate machine learning techniques including multi-armed bandits, reinforcement learning, LLM 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.
- Establish experimentation frameworks using advanced A/B testing, causal inference, and multivariate testing.
- Partner with Product and Growth Marketing to translate business hypotheses into machine learning problems.
- Mentor and coach senior engineers across data and ML organizations.
- Advocate for model monitoring, feature stores, reproducible training pipelines, and data governance.
Requirements
- 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 technology, recommendation engines, or consumer engagement.
- Extensive experience with large-scale data processing and distributed computing.
- Expert-level proficiency in Python, Scala, or Java.
- Experience with PyTorch, TensorFlow, JAX, or XGBoost.
- Experience with data and MLOps infrastructure such as Spark, Flink, Kafka, Snowflake, BigQuery, Ray, Kubeflow, MLflow, or SageMaker.
- Deep understanding of causal inference, uplift modeling, and robust statistical testing methodologies.
- Ability to connect algorithmic improvements to business growth metrics.
- Exceptional ability to explain complex technical architectures and algorithmic choices to non-technical stakeholders and executives.
Benefits
- Competitive salary and equity.
- Medical, dental, and vision insurance fully covered.
- Stipend for a remote or work-from-home setup, including laptop, headphones, and other work gear.
- Flexible hours and a supportive remote work environment.
- Unlimited vacation.
- 401(k) retirement plan.
- Wellness benefit.
- Daily lunch benefit.
- Fully remote work arrangement.
Tech Stack
Apache FlinkApache KafkaApache SparkGoogle BigQueryJavaMLflowPythonPyTorchScalaSnowflakeTensorFlowXGBoost
Categories
Growth EngineeringML Engineering