Staff Engineer, Machine Learning & Data Infrastructure
Posted Updated
Summary
Staff engineer leading architecture and hands-on development of the ML and data infrastructure behind OKX's risk and fraud prevention systems: optimizing model inference performance, building model serving/monitoring infrastructure, and connecting offline/online feature pipelines on Databricks, Spark, and cloud ML platforms. Hybrid role based in San Jose.
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 systems.
-
Set technical direction, mentor engineers, and lead delivery across ML, data engineering, cloud infrastructure, security, and product teams.
What We Look For In You
-
A 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, supported by measurable improvements in latency, throughput, utilization, or cost.
-
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.
-
Experience with the model lifecycle, including training/serving integration, validation, deployment, observability, and rollback.
-
Strong Python, SQL, and at least one backend or systems language such as Java, Scala, Go, or C++.
-
Ability to turn ambiguous requirements into clear architecture and deliver maintainable systems through hands-on engineering and technical leadership.
Nice to Haves
-
SageMaker, Alibaba Cloud PAI/EAS, or comparable ML platforms.
-
Inference optimization using tools such as ONNX Runtime, TensorRT, or Triton.
-
Delta Lake, MLflow, feature stores, Kafka, Flink, and low-latency data stores.
-
Fraud detection or financial risk systems.
-
Fluency in Mandarin
Perks & Benefits
-
Competitive total compensation package
-
L&D programs for employees' growth and development
-
Various team building programs and company events
-
Wellness and meal allowances
-
Comprehensive healthcare schemes for employees and dependants
-
More that we love to tell you along the process!
OKX Statement:
OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
The salary range for this position is $214,666 to 321,999
The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via OKX internal or external careers site.
#LI-SK1 #LI-HYBRID
Notice:
All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website.
Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX's Candidate Privacy Notice.
Skills
As published by greenhouse · 1 question
First Name, Last Name, Email, Phone, Resume/CV, Cover Letter, Location
- LinkedIn Profile optional