Join a Visionary Team Shaping the Future of Crypto

At OKX, we believe that cryptocurrency will redefine the future—empowering individuals with greater financial freedom and autonomy. As a leading global crypto exchange and developer of the widely trusted OKX Wallet, we provide millions of users with seamless access to crypto trading and decentralized applications (dApps). Trusted by hundreds of institutions, OKX combines cutting-edge innovation with robust security, underpinned by our transparent Proof of Reserves system.

Our global team is united by core values: _We Before Me_, _Do the Right Thing_, and _Get Things Done_. These principles shape our inclusive, high-performance culture—fostering collaboration, integrity, and continuous growth for every member of our team.

👉 Discover how you can lead in machine learning innovation within a fast-growing crypto environment.

Lead the Charge in Fraud Detection with Advanced Machine Learning

We are seeking a Senior or Staff Machine Learning Engineer to join our Risk Engineering Team, where your expertise will directly impact the security and integrity of one of the world’s most dynamic digital asset platforms. In this role, you'll focus on building intelligent systems for fraud detection, including bot detection, credit card chargeback prevention, and promotion abuse protection.

As a Tech Lead, you will oversee the full lifecycle of machine learning models—from design and deployment to ongoing optimization in production environments. You’ll also play a pivotal role in strengthening our data validation pipelines and developing real-time model performance monitoring systems. This is more than an engineering role—it’s an opportunity to lead, innovate, and scale ML infrastructure that protects millions of users worldwide.

Your Key Responsibilities

Design & Deploy Scalable ML Pipelines

Lead the development of end-to-end machine learning workflows designed for high-scale production use. Ensure systems are reliable, efficient, and capable of adapting to evolving threat landscapes.

Build Real-Time Model Monitoring Systems

Design and implement monitoring frameworks that track model accuracy, detect performance degradation, and flag anomalies in real time. Use insights to drive retraining strategies and improve predictive power.

Manage Full ML Lifecycle Operations

Oversee model versioning, A/B testing, automated retraining schedules, and rollback protocols. Maintain rigorous standards for reproducibility and traceability across all stages.

Strengthen Data Integrity

Collaborate with data engineers and risk analysts to enhance data validation pipelines. Ensure input data is accurate, consistent, and free from biases that could compromise model effectiveness.

Translate Business Needs into Technical Solutions

Work closely with product, compliance, and operations teams to understand emerging risks and convert them into actionable machine learning initiatives.

Mentor Emerging Talent

Provide technical leadership and coaching to junior engineers through code reviews, architecture discussions, and career development guidance. Help cultivate a culture of excellence and continuous learning.

What We’re Looking For

To succeed in this role, you should bring a strong foundation in machine learning engineering with proven experience in real-world deployments. Here's what matters most:

• 5+ years of hands-on experience in Machine Learning Engineering or related fields
• Expertise in ML Ops tools such as Flyte, Airflow, Kubeflow, or MLflow
• Proficiency in Python; familiarity with Java is a plus
• Deep understanding of data pipeline development, data validation, and performance monitoring systems
• Proven track record deploying and maintaining ML models in production-grade environments
• Solid grasp of CI/CD practices tailored for ML workflows
• Strong SQL skills and experience with databases like PostgreSQL, DynamoDB, message queues like Kafka, and caching systems like Redis
• Knowledge of model drift detection, A/B testing, and advanced evaluation metrics
• Exceptional problem-solving abilities in fast-moving, high-pressure settings
• Excellent communication skills and ability to collaborate across technical and non-technical teams
• Experience mentoring junior engineers and leading technical projects

Preferred Qualifications

While not required, candidates with the following will stand out:

• Hands-on experience with major cloud platforms (AWS, GCP, Azure, or Alibaba Cloud)
• Proficiency with containerization technologies like Docker and Kubernetes
• Prior work in fraud detection, especially in fintech or crypto domains
• Direct experience with bot behavior analysis, transaction risk scoring, or anomaly detection models

Why Join OKX?

OKX isn’t just building products—we’re shaping the future of finance. When you join us, you gain access to:

Competitive Compensation

A total rewards package including base salary, performance bonuses, and long-term incentives aligned with impact and growth.

Professional Development

Access to learning & development programs and education subsidies to support your technical and leadership journey.

Engaging Work Culture

Regular team-building events, global collaboration opportunities, and a diverse workplace that values inclusion and innovation.

👉 Explore how your machine learning expertise can thrive in a borderless financial ecosystem.

Transparent Compensation & Inclusive Hiring

The base salary range for this position is $126,000 to $273,923, depending on experience, location, and qualifications. Additional components may include performance-based bonuses and long-term incentive plans. Comprehensive medical, financial, and wellness benefits are provided based on role eligibility.

We welcome applicants from all backgrounds. OKX is committed to equal employment opportunity regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status. In accordance with the San Francisco Fair Chance Ordinance, we consider qualified applicants with arrest and conviction records.

Frequently Asked Questions

What does a typical day look like for a Machine Learning Tech Lead at OKX?

You’ll spend time designing model architectures, reviewing code, analyzing system performance metrics, and collaborating with risk analysts. Expect regular syncs with cross-functional teams and dedicated blocks for deep technical work.

Is this role remote or office-based?

OKX supports flexible work arrangements. Depending on location and team needs, this role may be remote, hybrid, or office-based.

How does OKX ensure model reliability in production?

We use automated monitoring for prediction drift, latency alerts, and data quality checks. Retraining pipelines are triggered based on thresholds, ensuring models stay accurate over time.

Do I need prior crypto experience?

While familiarity with blockchain or crypto is beneficial, it’s not mandatory. We value strong ML fundamentals and adaptability more than domain-specific knowledge.

What kind of fraud detection models are currently in use?

We employ a mix of supervised learning (e.g., gradient-boosted trees), unsupervised anomaly detection (e.g., autoencoders), and behavioral clustering techniques to identify suspicious patterns.

How big is the Risk Engineering team?

The team is growing rapidly but maintains agility. You’ll work in small squads focused on specific risk domains while contributing to shared infrastructure.

Ready to Build the Next Generation of Security Systems?

If you're passionate about applying machine learning to real-world security challenges—and want to do it at the forefront of the crypto revolution—this is your opportunity.

👉 Take the next step in your career by joining a team where innovation meets impact.