← Back to opportunities
H
Full-time

Senior Software Engineer, Machine Learning

Hive · CA / Remote (CA)
Pay
$124K–$188K / yr
Apply on company site
About the role

Hive is a marketing automation platform for event promoters, powering 1,500+ iconic events, festivals, venues, and promoters across North America. The R&D Data team builds systems to store and query production data at scale, powering Hive's products and making data accessible, reliable, and performant. As a Senior Data Engineer, you'll design and own a cloud-native big data platform handling audience data for millions of attendees and billions of interactions yearly, build ML infrastructure for models from experiment to production, and own full data pipelines while understanding business impact.

What you'll do
  • •Design and own a cloud-native big data platform handling audience data for millions of attendees and billions of interactions a year
  • •Design and own infrastructure for models from experiment to production — feature stores, training pipelines, model serving, and monitoring
  • •Drive the full pipeline stack end to end from Change Data Capture through validation, transformation, and denormalization
  • •Treat data as a product, defining SLAs and building for discoverability
  • •Build LLM-powered pipelines and autonomous agents that enrich, classify, and act on audience data at scale
  • •Connect technical decisions to business outcomes and communicate impact to non-technical audiences
What they're looking for
  • •8+ years of hands-on data engineering experience with large-scale distributed data and ML systems in production
  • •Core ML foundations (supervised/unsupervised, cross-validation, bias–variance, regularization, eval metrics)
  • •Feature engineering with Python ML tooling (pandas, scikit-learn; familiarity with PyTorch or TensorFlow)
  • •Production ML pipelines and feature datasets feeding model training and inference
  • •MLOps practices: experiment tracking, model versioning/registry, deployment, and monitoring for drift/data quality
  • •Strong foundations in distributed systems principles — partitioning strategies, consistency models, backpressure handling, fault tolerance
Skills
PythonDjangoClickhouseMySQLMongoDBAirflow or DagsterLLMs and Agentic SystemsMachine Learning

Found on workatastartup.com. Link checked Nov 9. Marquee links to the company's own application. We are not the employer.