The organization is looking to accelerate the global adoption of crypto and blockchain technology by building and maintaining core APIs that power user experience, including funding accounts, asset movement, fraud prevention, and transaction analysis.
Requirements
- Proficiency in Python; familiarity with Rust is a plus
- Experience designing and implementing large-scale batch data workflows (e.g., Pandas, Spark, Polars, SQL)
- Hands-on experience developing and operating real-time, low-latency streaming data pipelines (e.g., Apache Flink, Kafka, Beam)
- Proven experience building and maintaining AI/ML or data platforms at scale
- Solid understanding of MLOps concepts, including model lifecycle management, CI/CD for ML, feature stores, and data validation frameworks
- Experience with GenAI tools such as Langchain, LlamaIndex, and open source Vector DBs
- Hands-on experience with containerization and orchestration technologies such as Docker, Kubernetes, or Nomad
Responsibilities
- Design and implement Python services and libraries for real-time fraud detection and compliance monitoring
- Build scalable batch and streaming data pipelines for feature building, model inference, and training with strong data quality, latency, and reliability guarantees
- Develop and operate a developer-friendly ML platform, including feature stores, data validation tools, and automated model-training pipelines
- Support ML model lifecycle management from feature engineering to deployment, monitoring, and tuning
- Manage and optimize real-time data infrastructure using technologies such as Kafka, Apache Flink, and Kubernetes/Nomad
- Collaborate with Python and Rust engineers, data scientists, and business stakeholders
- Take end-to-end ownership of systems ensuring scalability, maintainability, and security
Other
- 5+ years of engineering experience in Data and/or AI/ML
- Strong communication and collaboration skills
- Commitment to building secure, reliable systems for mission-critical functions
- Mentor junior engineers and promote best engineering practices
- Stay up to date with MLOps, AI infrastructure, and data engineering trends to introduce innovative solutions
