okx · San Jose, California, United States
Skills: Python, Java, SQL
Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. About the Opportunity We are looking for an experienced engineer to lead the architecture and hands-on development of the ML and data infrastructure behind our risk and fraud prevention systems. You will help teams move models from experimentation into reliable production services, improve model execution performance, and build scalable data foundations for training, evaluation, and real-time decisions. What You’ll Be Doing Improve model inference latency, throughput, resource utilization, and cost. Profile the full prediction path —from feature retrieval and preprocessing to model execution — and deliver measurable improvements without unacceptable model-quality regressions. Build reusable infrastructure for model packaging, versioning, deployment, serving, monitoring, and rollback across cloud platforms and regions. Design and optimize offline data pipelines on Databricks, Apache Spark, and warehouse/lakehouse technologies, addressing data modeling, partitioning, joins, shuffles, skew, incremental processing, and cost. Connect offline and online feature pipelines, ensuring point-in-time correctness, consistent feature definitions, freshness, lineage, and reproducible backfills. Evolve reliable feature services and data integrations supporting risk models and decision…
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