Sr. Software Engineer, Machine Learning & Data Infrastructure

Posted 15 Hours Ago
Be an Early Applicant
San Jose, CA, USA
Hybrid
179K-268K Annually
Senior level
Fintech • Financial Services • Cryptocurrency
The Role
Build and operate machine learning and data infrastructure for risk and fraud prevention systems. Improve model inference performance, deploy and monitor models across cloud platforms, and develop offline and online feature pipelines. Optimize Databricks and Spark data processing, ensure feature correctness and reproducibility, and maintain reliable feature services. Own projects and operational issues while collaborating with ML, data engineering, cloud infrastructure, security, and product teams.
Summary Generated by Built In
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 a seasoned engineer to build and improve the ML and data infrastructure behind our risk and fraud prevention systems. You will work hands-on to move models from experimentation into reliable production services, improve model execution performance, and develop data pipelines that support training, evaluation, and real-time decisions. You will take ownership of your work, identify improvements proactively, and deliver with limited guidance
What You’ll Be Doing
  • Improve model inference latency, throughput, resource utilization, and cost. Profile the prediction path—from feature retrieval and preprocessing to model execution—and implement measurable improvements while preserving model quality.
  • Build and maintain infrastructure for model packaging, versioning, deployment, serving, monitoring, and rollback across cloud platforms and regions.
  • Develop and optimize offline data pipelines using Databricks, Apache Spark, and warehouse or lakehouse technologies. Address data modeling, partitioning, joins, shuffles, skew, incremental processing, and cost.
  • Work on offline and online feature pipelines, supporting point-in-time correctness, consistent feature definitions, freshness, lineage, and reproducible backfills.
  • Build and maintain reliable feature services and data integrations for risk models and decision systems.
  • Take ownership of projects and operational issues, communicate progress and tradeoffs, and collaborate with ML, data engineering, cloud infrastructure, security, and product teams.
  • Contribute to technical discussions, share knowledge, and help teammates through code reviews and collaboration.
 
What We Look For In You
  • Experience building and operating distributed systems, ML infrastructure, or data platforms, with ownership of meaningful production components.
  • Hands-on experience improving production model performance, such as latency, throughput, resource utilization, or cost.
  • Strong experience with 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 and serving integration, validation, deployment, observability, and rollback.
  • Strong Python and SQL skills, plus proficiency in at least one backend or systems language such as Java, Scala, Go, or C++.
  • Ability to work independently through loosely defined problems, make sound implementation decisions, and deliver maintainable systems with limited guidance.
 
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 $178,888 to $268,333
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.
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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 Required

  • Experience building and operating distributed systems, ML infrastructure, or data platforms, including ownership of meaningful production components.
  • Hands-on experience improving production model performance, including latency, throughput, resource utilization, or cost.
  • Strong experience with Databricks and Apache Spark or comparable offline data platforms, including distributed query optimization, storage layouts, data correctness, and workload cost management.
  • Experience with the machine learning model lifecycle, including training and serving integration, validation, deployment, observability, and rollback.
  • Strong Python and SQL skills.
  • Proficiency in at least one backend or systems language such as Java, Scala, Go, or C++.
  • Ability to work independently through loosely defined problems and deliver maintainable systems with limited guidance.
  • Experience with SageMaker, Alibaba Cloud PAI/EAS, or comparable ML platforms.
  • Experience with inference optimization using ONNX Runtime, TensorRT, or Triton.
  • Experience with Delta Lake, MLflow, feature stores, Kafka, Flink, and low-latency data stores.
  • Experience with fraud detection or financial risk systems.
  • Fluency in Mandarin.

OKX Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about OKX and has not been reviewed or approved by OKX.

  • Fair & Transparent Compensation — Pay is considered competitive or above market, especially in engineering, product, and legal roles across major hubs. This positioning is consistently cited as a major attraction for candidates.
  • Healthcare Strength — Role descriptions indicate comprehensive medical, dental, vision, life, and disability coverage, with employer-paid premiums in some cases. Health coverage is highlighted alongside core benefits like PTO and parental leave.
  • Wellbeing & Lifestyle Benefits — Allowances for education and fitness, meal perks and snacks, team-building budgets, and structured learning programs are described across locations. These extras enhance the total rewards package beyond base pay.

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The Company
HQ: Singapore
1,073 Employees
Year Founded: 2017

What We Do

Founded in 2017, OKX is one of the world’s leading cryptocurrency spot and derivatives exchanges. OKX innovatively adopted blockchain technology to reshape the financial ecosystem by offering some of the most diverse and sophisticated products, solutions, and trading tools on the market. Trusted by more than 20 million users in over 180 regions globally, OKX strives to provide an engaging platform that empowers every individual to explore the world of crypto. In addition to its world-class DeFi exchange, OKX serves its users with OKX Insights, a research arm that is at the cutting edge of the latest trends in the cryptocurrency industry. With its extensive range of crypto products and services, and unwavering commitment to innovation, OKX’s vision is a world of financial access backed by blockchain and the power of decentralized finance.

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