Senior Software Engineer, ML/AI Platform
Senior Software Engineer on the ML Platform team building and operating data, tooling, serving, and inference layers for a PB-scale feature store and ML lifecycle at a high-growth AI marketing company.
About the job
What You’ll Accomplish
- Unlock offline & real-time access to trillions of data points for our ML and Data Science teams.
- Manage, expand, and optimize our feature store that enables feature engineering, multi-TB scale training jobs, and offline / real-time inferencing.
- Support PB scale data operations on the feature store using Apache Spark, Spark Structured Streaming, Kafka, and Ray.
- Partner with other teams and business stakeholders to deliver ML and AI initiatives.
Your Expertise
- 5+ years working in Data Engineering / MLOps, with experience building and maturing pipelines of a PB-scale feature store.
- Deep experience with Apache Spark, Spark Streaming, and Ray Data for building data pipelines for ML use cases.
- Understanding of the correlation between data cardinality, query plans, configuration settings, hardware, and their impact on data pipeline performance.
- Experience creating infrastructure for training ML models and fine-tuning LLMs.
- Understanding of key differences between online and offline ML inferences and critical elements for success with each.
What We Use
- Infrastructure runs primarily in Kubernetes hosted in AWS’s EKS.
- Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm.
- Backend: Java / Spring Boot microservices, built with Gradle, coupled with DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS.
- Frontend: React and TypeScript, using GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright.
- Automation: Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas.
Skills
Spark, Spark Streaming, Ray Data, Kubernetes, Aws Eks, Python, PyTorch, TensorFlow, Metaflow, Kafka
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