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GM
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OKX

Machine Learning Engineer - Risk & AI

San Jose, CA, United States

The salary range for this position is $214,666 to $321,999

Apply on job-boards.greenhouse.io About employer

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Job details

Pay: The salary range for this position is $214,666 to $321,999
Posting language: English
Posted: Nov 10, 2026

Original job description

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

Building machine learning systems for risk at a global crypto exchange is fundamentally different from conventional ML engineering. The data spans on-chain activity, fiat deposits and withdrawals, trading behaviour, account access patterns, device intelligence, identity information, and customer interactions - signals that very few organizations can analyze together.

The problems are complex, adversarial, and constantly evolving. Models must identify emerging fraud patterns, scams, account takeovers, payment abuse, and other forms of financial risk while minimizing disruption to legitimate customers. Success is not measured only through offline model metrics. It is measured through prevented losses, improved approval rates, reduced false positives, faster investigations, and more reliable customer experience.

This role sits within a multidisciplinary risk team of machine learning engineers, data scientists, risk strategy specialists, analytics engineers, product managers, and operations teams. You will work across the full ML lifecycle - from problem formulation, feature engineering, and model development to real-time deployment, monitoring, experimentation, and continuous iteration.

You will also help shape how AI is used across the risk organization. LLM-assisted development, automated model workflows, AI-powered investigations, and intelligent review agents are part of the team’s daily work. We are looking for engineers who already use these tools effectively and can help establish safe, scalable, and production-ready AI practices.

What You’ll Be Doing

We’re looking for a Machine Learning Engineer to build models and AI tools that help detect fraud and protect users at a global crypto exchange. You’ll apply deep learning and XGBoost, develop practical AI agents, and use AI coding tools in your daily work.

• Build, evaluate, and deploy machine learning models for fraud and risk detection.

• Improve data quality, features, and model performance, balancing fraud detection with customer experience.

• Develop AI agents to support investigations, summarize cases, retrieve evidence, and automate routine workflows.

• Use AI coding tools to accelerate development, testing, and debugging while reviewing and validating their output.

• Work with engineering, product, and risk teams to deploy solutions and monitor their impact.

What We Look For In You

• A strong foundation in machine learning, with hands-on experience in deep learning and tree-based models such as XGBoost or LightGBM.

• Strong Python skills and experience training, evaluating, and deploying models.

• Some practical experience building AI agents or LLM applications, including tool calling, retrieval, or workflow automation. Prototypes and personal projects are welcome.

• Regular use of AI coding tools, with the ability to understand, test, and improve generated code.

• Familiarity with databases and data pipelines for preparing training data and supporting ML workflows.

• Good problem-solving, communication, and collaboration skills.

Nice to Haves

• Experience in account takeover (ATO), scam detection, or other fraud and risk use cases.

• Experience with LLM training, fine-tuning, evaluation, and alignment.

• Experience with reinforcement learning algorithms and their practical implementation.

• Experience with real-time ML systems, imbalanced datasets, or model explainability.

• Prior fraud or risk experience is helpful

• 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.

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.

Apply on job-boards.greenhouse.io About employer

More about this job

Skills

Machine learning
ML
Customer experience
Deep learning
XGBoost
Fraud detection
Debugging
Python
Problem solving
Communication skills
Collaboration

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Jobs in the United States