Staff Machine Learning Engineer, OKX
$214.7-322k
Office located in San Jose, CA
Cryptocurrency trading app
Posted today
Cryptocurrency trading app
1001+ employees
Posted today
$214.7-322k
Office located in San Jose, CA
1001+ employees
Company mission
To take care of our team, promote and advance crypto globally, and empower every individual in the world.
Role
Who you are
- Significant professional experience in machine learning engineering, applied data science, or a closely related field, with a strong record of taking models from prototype to production. Scope and level will be calibrated based on experience
- Strong Python skills and hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, XGBoost, LightGBM, or scikit-learn
- Strong knowledge of applied machine learning fundamentals, including supervised learning, anomaly detection, representation learning, class-imbalanced modeling, model calibration, and evaluation under changing data distributions
- Demonstrable fluency with AI-assisted engineering. You regularly use LLM coding tools, have built AI-integrated workflows or applications, and understand both the productivity benefits and the security, reliability, and governance risks
- Familiarity with model explainability techniques such as SHAP, feature attribution, reason-code generation, and model scorecards
- Hands-on experience designing and deploying production LLM agents, including agentic workflows, tool calling, retrieval-augmented generation, prompt and context management, structured output generation, and multi-step task orchestration
- Experience integrating LLM agents with internal systems, APIs, databases, search tools, case-management platforms, or decision engines to automate complex operational workflows
- A strong understanding of LLM-agent evaluation and reliability, including hallucination control, grounding, observability, permissions, failure handling, human review, latency, and cost optimization
- Experience building AI agents for fraud, risk, compliance, customer operations, cybersecurity, or other high-stakes domains is a meaningful advantage
- Strong communication and collaboration skills, with the ability to work effectively with engineers, data scientists, risk specialists, product managers, operations teams, and legal or compliance stakeholders
What the job involves
- Design, build, and deploy machine learning models for risk use cases such as payment fraud, account takeover, scam detection, deposit and withdrawal risk, promotional abuse, customer risk assessment, and transaction monitoring
- Own production ML systems end to end, including feature pipelines, training workflows, model serving, decision integrations, monitoring, alerting, drift detection, retraining, and incident response
- Partner with risk strategy and product teams to translate models into effective production controls, including approval, rejection, review, cooldown, limit adjustment, account restriction, and other risk mitigation actions
- Work closely with risk operations teams to understand investigation workflows, incorporate reviewer feedback, improve model explainability, and continuously refine labels and training data
- Apply AI-assisted development throughout the engineering workflow, using LLM coding tools to accelerate implementation, testing, debugging, analysis, and documentation while maintaining appropriate security and review standards
- Develop AI-powered risk capabilities such as investigation agents, case summarization, evidence collection, review recommendations, alert triage, suspicious-entity mining, and automated decision support
- Take research-stage models into reliable production systems by validating feature logic, reviewing data quality, addressing latency and scalability constraints, and ensuring consistency between offline training and online inference
- Ensure models and decision systems are explainable, traceable, and well documented so that model outputs can be understood by risk operations, product stakeholders, internal governance teams, and regulators where applicable
- Design, build, and deploy LLM-based agents for risk operations and investigation workflows, including case triage, evidence retrieval, transaction analysis, alert summarization, review recommendations, and automated action orchestration
- Develop production-grade agent architectures using tool calling, retrieval-augmented generation, workflow orchestration, structured outputs, memory, guardrails, and human-in-the-loop controls
- Build evaluation frameworks for LLM agents, measuring factual accuracy, task completion, decision consistency, latency, cost, reviewer acceptance, and operational impact. Ensure LLM agents operate safely in a regulated risk environment by implementing permission controls, audit logs, data privacy protections, prompt and tool security, fallback mechanisms, and clear escalation paths
Our take
While cryptocurrency holds the promise of freedom in personal finances and the possibility of large financial rewards through trading, it can be intimidating to get started. OKX, a long-standing crypto currency exchange, exists to solve that problem, removing the knowledge barriers to cryptocurrency trading with an easy-to-use, all in one platform.
OKX is one of the larger cryptocurrency exchanges, though it is a bit smaller than the market leaders Binance and Coinbase Exchange. Where it shines is in the sheer range of its services, which are designed to be versatile enough for any user, ranging from a crypto exchange to NFT and decentralised finance investment products. With a reputation for security and reliability, it has a user base of over 50+ million active accounts in over 180 countries.
OKX is using its structural position in cryptomarkets to help support the entire sector, announcing a market recovery fund to protect crypto firms facing collapse following the FTX crisis. Additionally, it is expanding into Web3 gaming with a 2023 partnership with Thirdverse, further increasing the scope of its offering to its client base. As long as it can continue to weather the tough market conditions for cryptocurrency, it should maintain its excellent position to continue its growth.
Freddie
Company Specialist at Welcome to the Jungle
Company
Leadership
Star Xu
(Founder & CEO)Previously an Engineer at Yahoo before becoming the Chief Technology Officer at DocIn. They later founded OKX and has recently reclaimed the title of CEO
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