Staff Machine Learning Engineer (Modeling), Support at Block in Seattle, WA, United States of America

Job description

• Block's Support ML Modeling team is a central driver of innovation in customer support experiences across our entire ecosystem—including Cash App, Square, and other business units. We are dedicated to advancing the state of intelligent, automated support through machine learning and generative AI. From customer-facing chatbots to smart internal tools for agents, our team builds high-impact, scalable systems that improve support quality, efficiency, and accessibility.
• We're building the future of support at Block: one powered by AI, voice interfaces, and smart automation. We're looking for candidates with a passion for intelligent systems, practical ML experience, and a desire to build product-driven solutions. Our ideal candidate is a leader in the field, with a proven track record of building ML systems that can accelerate our ability to scale our conversational AI initiatives.

Responsibilities

• Lead the end-to-end delivery of multiple ML initiatives, from planning and design through rollout, documentation, and long-term maintenance
• Partner strategically with risk, product, engineering, design, and operations leaders to define and drive long term ML roadmaps, informed by domain expertise and industry trends
• Guide the team’s direction, identifying new ML/AI opportunities and advising leadership on strategic tradeoffs and opportunities
• Drive R&D efforts exploring next-generation chatbot architectures using LLMs, RAG, fine-tuning, and real-time inference
• Design, deploy, and maintain ML models powering conversational agents including support chatbots across Cash App, Square, and other Block products
• Develop ML-powered tools and real time recommendation systems that enhance support agent effectiveness and customer outcomes
• Act as the technical representative for your team’s systems and programs, clearly communicating work and results to stakeholders, cross-functional partners, and external audiences

Requirements

• 10+ years of experience in machine learning, applied AI, or product ML roles, with deep technical expertise
• Demonstrated leadership capabilities, with the ability to influence and align cross-functional teams while directly shaping the work of peers through communication, context sharing, and technical guidance
• A track record of delivering organizational wide impact, shaping systems, frameworks, or initiatives that raise the bar across multiple teams or functions
• Proven ability to ship end to end ML features from problem framing through deployment and long-term maintenance
• Demonstrated experience with language models, dialog systems, or generative AI in production
• Strong foundation in NLP, deep learning, or ML infrastructure best practices.
• Excellent communication skills, with the ability to represent the team’s work to leadership and stakeholders
• Enthusiasm for R&D and pushing the boundaries of applied AI to transform conversational systems
• Python, PyTorch, TensorFlow, or JAX

Skills

Required

• Machine learning
• Applied AI
• Product ML
• Leadership
• Communication
• NLP
• Deep learning
• ML infrastructure
• Language models
• Dialog systems
• Generative AI in production
• End-to-end ML feature development

Benefits

• Every benefit we offer is designed with one goal: empowering you to do the best work of your career while building the life you want. Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning are just some of our offering. Check out our other benefits at Block.
• Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.
• To find a location’s zone designation, please refer to this resource. If a location of interest is not listed, please speak with a recruiter for additional information.
• $276,800—$415,200 USD