Senior Machine Learning Engineer, Platform
Block (Square) · Bay Area, CA, United States of America
About this role
**Block — Senior Machine Learning Engineer, Platform** Block is one company built from many brands—Square, Cash App, Afterpay, TIDAL, Spiral, and Proto—united by the purpose of economic empowerment. We’re remote-first and use intelligence at the center of everything we do. ## The Role Block’s Machine Learning (ML) Platform team builds shared infrastructure that helps teams develop, evaluate, deploy, and monitor models and automated decision systems for use cases such as fraud detection, recommendations, and underwriting. You’ll work closely with applied ML teams to shape the roadmap, improve existing services, and build new platform capabilities—while deepening your expertise across the ML lifecycle, influencing system designs, and mentoring other engineers. ## You Will - Design, build, and operate shared ML infrastructure, including feature stores, rules engines, model hosting & inference, training infrastructure, and offline model evaluation. - Lead the design and delivery of large-scale distributed systems, balancing response time, throughput, data consistency, availability, and cost. - Partner with applied ML teams and internal customers to understand needs and turn them into reusable platform capabilities; use feedback to set roadmap and priorities. - Build reliable services through automated testing, monitoring, capacity planning, and safe deployments. - Participate in the oncall rotation for mission-critical systems; lead incident response and reviews; fix root causes to prevent repeats and reduce manual support. - Build self-service interfaces, libraries, tools, and documentation to help teams develop models, move them into production, and understand performance. - Mentor engineers, guide design reviews, and share practices to maintain reliable systems. ## You Have - 8+ years of experience in software development and/or machine learning, with a focus on internal platforms or infrastructure. - Hands-on experience building and operating ML infrastructure, with depth in one or more areas such as feature stores, rules engines, model hosting & inference, or training infrastructure. - Deep understanding of ML-backed solution architectures and the ML lifecycle—from data gathering and training to model evaluation, MLOps, and productionizing models (classical ML and deep learning/LLMs). - Experience designing and operating large-scale distributed systems, including failure modes, data correctness, and performance/capacity management. - Experience operating mission-critical services (oncall, incident response, and reliability improvements). - Experience leading complex technical work from unclear starting points through delivery (problem definition, testing ideas, choosing designs, planning cross-team work, and validating results). - Experience working with platform customers: explaining technical choices/trade-offs and mentoring engineers. - Experience with major cloud vendors for high-scale production use cases. - Strong communication skills with technical and non-technical stakeholders. - Ruthless pragmatism when solving new and unconventional problems. ## Technologies We Use and Teach - Kotlin/Java, Go, Python, TypeScript, React - gRPC, Protocol Buffers - AWS (SageMaker, EC2, EKS, Dynamo), Databricks (Spark) - NVIDIA Triton, vLLM, ONNX ## Equal Opportunity & Accessibility Block is an equal opportunity employer. They evaluate applicants without regard to identity or legally protected class. They also provide an inclusive intervie
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