Description:

Attentive is seeking a Senior Machine Learning Operations Engineer, Feature Store Developer to join their MLOps team.
The role involves enabling Attentive’s Machine Learning practice to impact their AI product suite through tools for training, inference, and deployment of ML models.
The engineer will build and maintain a foundational ML platform that spans the full ML lifecycle for ML engineers and data scientists.
Responsibilities include unlocking offline and real-time access to trillions of data points, managing and optimizing the feature store, and supporting PB scale data operations using technologies like Apache Spark and Kafka.
The engineer will partner with other teams and business stakeholders to deliver ML and AI initiatives.

Requirements:

Candidates must have 5+ years of experience in Data Engineering or MLOps, specifically in building and maturing pipelines for a PB-scale feature store.
Deep knowledge of Apache Spark, Spark Streaming, and Ray Data is required, along with experience in building data pipelines for ML use cases.
Understanding the correlation between data cardinality, query plans, configuration settings, and hardware is essential for optimizing data pipeline performance.
Experience in leading the rollout and operationalization of feature stores such as Tecton or Feast is necessary.
Candidates should understand the differences between online and offline ML inferences and the critical elements for success in each.

Attentive offers competitive perks and benefits, including health and wellness programs, equity options, and other resources to support employees in bringing their best selves to work.
The US base salary range for this position is $144,840 - $210,000 annually, plus equity and benefits.
Attentive promotes a diverse and inclusive workplace, providing equal employment opportunities and reasonable accommodations for candidates with disabilities.