ML Platform Engineer

Responsibilities

• We have a bold mission to empower everyone to build wealth with easy, safe, and free access to financial systems. You will have the opportunity to grow your career by collaborating with a team of outstanding talents and state-of-the-art technology to build a lasting, positive future for millions
• Build and own production-grade infrastructure for real-time ML, feature serving, and critical decisioning systems
• Design data‑intensive platforms that process high-volume event streams with low latency and strong reliability
• Define reusable engineering patterns that help teams build, ship, operate, and scale platform capabilities reliably
• Build and operate data streaming and serving platforms for sub‑second algorithms in mission‑critical systems
• Work closely with ML, data, backend, and product teams to turn complex requirements into simple, reliable systems
• Mentor peers, share knowledge, and help raise the quality of engineering ownership across the team

Nice to Have

Experience with ClickHouse, Kafka, Flink, or similar technologies for stream processing and high-performance SQL workload. Able to work across infrastructure, data, backend, and ML systems, translating ambiguous requirements into simple, reliable platform capabilities. Solid understanding of distributed systems, networking, latency, reliability, backpressure, and operational trade-offs. Ability to make pragmatic trade‑offs across performance, scalability, cost, and reliability in large‑scale production systems. Strong interpersonal skills, self‑starter with high autonomy, and a focus on knowledge sharing and team growth. Strong background in software, systems, or infrastructure engineering, with hands-on experience building and operating production‑grade services on Kubernetes.