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Staff Software Engineer – Machine Learning Infrastructure
| Company | OKX |
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| Location | San Jose, CA, USA |
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| Salary | $126000 – $273923 |
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| Type | Full-Time |
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| Degrees | |
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| Experience Level | Senior, Expert or higher |
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Requirements
- At least 5+ years of experience in Machine Learning Engineering
- Strong experience with ML Ops frameworks and tools (e.g., Flyte, Airflow, Kubeflow, MLflow, etc)
- Proficiency in Python and familiarity with Java
- In-depth knowledge of data validation, data pipeline development, and performance monitoring systems
- Extensive experience in deploying and managing machine learning models in production environments
- Solid understanding of CI/CD practices for machine learning workflows
- Experience with SQL and familiarity with common data products such as PostgreSQL, DynamoDB, Kafka, and Redis
- Familiarity with A/B testing, model drift detection, and advanced monitoring techniques
- Strong problem-solving skills and ability to work in a fast-paced environment
- Excellent communication and collaboration skills
- Proven experience coaching and mentoring junior engineers
- Familiar with at least one major cloud services, like AWS, CGP, Azure or Alicloud
Responsibilities
- Lead the design, development, and deployment of end-to-end machine learning pipelines for production use, ensuring scalability, reliability, and performance
- Design and implement a robust model performance monitoring system to track and evaluate the success of models in real-time, identifying areas for improvement
- Manage and optimize the full lifecycle of ML models, including versioning, retraining, and monitoring model performance in production
- Collaborate with cross-functional teams to implement and improve data validation pipelines, ensuring the integrity and quality of data used in ML models
- Work closely with cross-functional teams to understand business requirements and translate them into technical solutions
- Provide technical leadership and mentorship to junior team members, supporting their professional development through coaching and code reviews
Preferred Qualifications
- Experience in fraud detection, specifically in areas like bot detection, credit card chargeback prevention, and promotion abuse protection, is highly desirable
