Senior Machine Learning Engineer

The machine learning platform provides tools and services for building feature transformations, distributed deep learning models, model lifecycle management, counterfactual simulation and budget optimization for continuously improving user engagement and revenue generation for our 100 million+ Credit Karma users.

This role is also exciting because you'll provide capabilities for feature engineering, monitor feature quality and serve features at scale for the models.

• We're a team of Machine Learning Engineers continuously building and improving Credit Karma's Machine Learning Platform. Our mission is to help improve user experience through better personalization.
• We build ML Infrastructure and own a custom MLOps framework that helps data scientists develop, deploy, and manage models at scale.
• We develop, scale, and innovate on a platform for machine learning, prediction serving, and personalized recommendation serving.

• The ML Platform provides tools and services for feature engineering, monitoring feature quality, serving features at scale, building feature transformations, training Deep Learning and AI models, continuous training/refresh, and model lifecycle management.
• We partner with data scientists to design, develop, and deploy platform capabilities to build AI.
• You will use a variety of technologies such as BigQuery, Apache Beam, Tensorflow, Keras, Scikit-Learn and Apache Airflow on Big Data.
• Technologies for production serving and personalization include Scala, Finagle, BigTable, GRPC, TF-Serving, Thrift, Kubernetes, Splunk and Grafana.

• Dynamic server-side OOP languages; Scala, Java, C++, PHP, Python, Perl, Ruby, or similar; design patterns, algorithms, statistics, probability theory, machine learning, artificial intelligence, programming languages, networking and operating systems; web application internals and common technologies; deployment strategies
• production infrastructure; Kafka, BigQuery, Dataflow, Spark, AI Platform, Akka-Http, GRPC, BigTable, JavaScript frameworks; application scalability at any application tier; SQL, relational database schema design and ORM technologies; and Agile/Scrum practices.

What we would like to see:

• Master's degree in Computer Science, Engineering, Computer Information Systems, Mathematics, Physics, or a related field
• Modern data technologies include technologies such as in-memory, distributed and serverless processing (e.g. spark/dataflow/cloud-functions), key/value vs. document vs. column oriented datastores (e.g. bigquery, bigtable, cloud-search), message queues (kafka/pub-sub), elastic scaling (kubernetes, instance-groups), etc
• Modern machine learning and optimization technologies include familiarity with toolkits like sklearn, scipy, tensorflow and pytorch

• Medical and Dental Coverage
• Retirement Plan
• Commuter Benefits
• Wellness perks
• Paid Time Off (Vacation, Sick, Baby Bonding, Cultural Observance, & More)
• Education Perks
• Paid Gift Week in December