Senior Machine Learning Engineer

What You'll Do

• Develop Data Scientist and Analyst-friendly self-service tooling and frameworks to explore new data sources, extract new features, and train, test, deploy, and monitor models. 
• Optimize the model development and software development life cycles.
• Maximize quality of models, services, and tooling with unit testing, integration testing, dry run and blue-green deployment, infrastructure-as-code, automation, observability, and fault tolerance.
• Write and review design documents, perform code reviews, and weigh in on implementation choices from other technical teams. 
• Collaborate with and support cross-functional teams (Product, Data Platform, Credit, and Business Development).

What You'll Need

• 5+ years of backend software experience in consumer scale applications, at least 4 of them with Python
• 2+ of those years in real-time streaming data (Kafka, Kinesis, Beam, Flink, Spark Streaming)
• Experience autonomously building machine learning or causal inference models to solve business problems.
• Proficiency with machine learning tools and tech (Jupyter, Pandas, Scikit-Learn, Xgboost, Tensorflow, Pytorch, Hugging Face).
• Strong database experience, both relational and non-relational (MySQL, PostgreSQL, Cassandra, HDFS, Snowflake, Druid).
• Strong hands-on experience in cloud computing (AWS, GCP, Azure, Kubernetes).
• Experience with batch processing platforms (Airflow, Metaflow).
• Experience with API development for mobile/web use (REST, GraphQL, gRPC, Protocol Buffers).
• Strong collaboration experience with Data Science, Analytics, other Engineering teams, and business stakeholders.
• Knowledge of scalable algorithms.
• Prefer advanced degree in computer science, math, or related field.