Staff Engineer, Machine Learning & Data Infrastructure

About the role

OKX, a crypto exchange and developer of OKX Wallet, is looking for an experienced engineer to lead the architecture and hands-on development of the machine learning and data infrastructure behind its risk and fraud prevention systems. The role helps teams move models from experimentation into reliable production services, improves model execution performance and builds scalable data foundations for training, evaluation and real-time decisions. The position is based in San Jose, California, and is listed as hybrid.

Key responsibilities

• Improve model inference latency, throughput, resource utilization and cost by profiling the full prediction path, from feature retrieval and preprocessing to model execution.
• 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, covering 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.
• Evolving reliable feature services and data integrations supporting risk models and decision systems.
• Set technical direction, mentor engineers and lead delivery across ML, data engineering, cloud infrastructure, security and product teams.

Required profile

• Record of building and operating large-scale distributed systems, ML infrastructure or data platforms, with technical ownership across teams.
• Hands-on experience optimizing production model performance, with measurable improvements in latency, throughput, utilization or cost.
• Experience with the model lifecycle, including training/serving integration, validation, deployment, observability and rollback.
• Ability to turn ambiguous requirements into clear architecture and deliver maintainable systems through hands-on engineering and technical leadership.

Required skills

• Deep understanding of Databricks and Spark, or comparable offline data platforms, including execution plans, distributed query optimization, storage layouts, data correctness and workload cost management.
• Strong Python, SQL and at least one backend or systems language such as Java, Scala, Go or C++.
• Nice to have: SageMaker, Alibaba Cloud PAI/EAS; ONNX Runtime, TensorRT or Triton; Delta Lake, MLflow, feature stores, Kafka, Flink, low-latency data stores; fraud detection or financial risk systems; fluency in Mandarin.

What we offer

• Salary range of $214,666 to $321,999, depending on knowledge, skills, experience and market location.
• Performance bonus and long-term incentives may be provided.
• Lamp and L&D programs, team building programs and company events.
• Wellness and meal allowances, and comprehensive healthcare for employees and dependants.