Sr. Software Engineer, Machine Learning & Data Infrastructure
Okx
·Today
- Salary
- $179k – $268k/yr
- Location
- San Jose, California, United States
- Department
- Engineering
- Seniority
- Senior
- Source
- Greenhouse
Description
Who We Are
About the Opportunity
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
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SageMaker, Alibaba Cloud PAI/EAS, or comparable ML platforms.
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Inference optimization using tools such as ONNX Runtime, TensorRT, or Triton.
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Delta Lake, MLflow, feature stores, Kafka, Flink, and low-latency data stores.
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Fraud detection or financial risk systems.
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Fluency in Mandarin
Perks & Benefits
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Competitive total compensation package
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L&D programs for employees' growth and development
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Various team building programs and company events
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Wellness and meal allowances
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Comprehensive healthcare schemes for employees and dependants
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More that we love to tell you along the process!
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