About the Job:
Building the Future of Crypto
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At the company, we are a world-class team united by our commitment to discover and unlock the potential of crypto and blockchain technology. We are a mission-focused company rooted in crypto values, aiming to accelerate global adoption of crypto for financial freedom and inclusion. Our culture attracts talented crypto experts who are dedicated to building premium products for traders, institutions, and newcomers alike.
As part of the company’s Data organization, you will own the Machine Learning platforms and systems utilized across the company, operating at a company-wide scope. Your role will involve collaborating closely with product, engineering, data science, security, and compliance partners to ensure scalable, observable, and compliant ML systems.
Key Responsibilities:
- Set long-term technical direction for the company’s AI/ML strategy, influencing various teams and initiatives.
- Own the architecture and evolution of core AI/ML systems, including training, feature management, serving, experimentation, and monitoring.
- Lead efforts to standardize ML development and operational practices across the company.
- Drive the design and delivery of complex, high-impact ML systems for use cases such as fraud, risk, personalization, and recommendations.
- Partner with senior engineering, product, and data leaders to identify ML opportunities that enhance scalability and efficiency.
- Balance hands-on contributions with architectural leadership and design reviews.
- Mentor staff and senior engineers, shaping technical culture and elevating overall ML engineering quality.
Qualifications:
- 10+ years of experience building and operating large-scale production Machine Learning systems.
- Proven record of owning ML platforms or infrastructures that serve multiple teams or products.
- Strong system design skills with experience in making long-term architectural trade-offs.
- Expert-level proficiency in Python and experience with additional languages like Scala, Go, or Rust.
- Deep hands-on experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and model lifecycle management.
- Extensive experience in MLOps practices, including CI/CD, model monitoring, and reliability.
- Strong background in data-intensive and distributed systems (Spark, object storage, large-scale batch and streaming).
- Ability to lead through influence, mentor engineers, and communicate technical strategy effectively.
Language Requirements:
Fluency in English; proficiency in other languages is a plus as team members communicate in over 50 languages.
The company is an equal opportunity employer and values diversity. We encourage applicants from all backgrounds to apply, regardless of whether they meet all the listed requirements.
