Senior ML/Data Engineer

What you'll do

• Design and operate streaming ingestion, high-volume time-series storage, and low-latency feature-serving infrastructure.
• Build graph data models and systems for data provenance, tenant isolation, observability, and ML evaluation.
• Partner with data scientists, ML engineers, and sports experts to turn requirements into reliable production systems.

What they ask for

• 5+ years of full-time professional software or data engineering experience, excluding internships, placements, coursework, and academic projects.
• Proven experience designing, building, and operating production data infrastructure at scale, including time-series data and real-time or streaming ingestion.
• Experience designing graph data models or schemas and designing or operating multi-tenant systems with tenant-level isolation.
• Strong Python and SQL skills; experience with production reliability, scalability, observability, and data correctness.

Nice to have

• Professional experience with Go.
• Experience with probabilistic evaluation, calibration, causal inference, simulation, wearable sensors, knowledge graphs, LLM or AI evaluation, AWS, or listed API and database technologies.

Pay

$157,945 to $259,480 USD per year, target total compensation (inclusive of base salary and a target incentive plan).

Tools

InfluxDB, TimescaleDB, Prometheus, ClickHouse, Kafka, Kinesis, Flink, Spark Streaming

AI focus

Build data foundations for AI agents and machine-learning training, inference, and evaluation; develop ML evaluation infrastructure for reliability, calibration, and performance.