Staff Machine Learning Engineer, Support

Block; Seattle (WA); Remote; USD 210,000 - 270,000; Full time

Benefits offered by this job

Remote work

Medical insurance

Flexible time off

Retirement savings plans

Modern family planning benefits

Job summary

Block is seeking a senior ML leader to own end-to-end delivery of multiple AI initiatives, from planning to rollout and long-term maintenance. You will collaborate with risk, product, engineering, design, and operations leaders to shape long-term ML roadmaps and guide teams toward strategic opportunities in conversational AI platforms.

The role emphasizes R&D in chatbot architectures, real-time inference, and deploying models across Block products, with a focus on improving customer outcomes

Qualifications

• 10+ years of experience in machine learning, applied AI, or product ML, with deep technical expertise.
• Demonstrated ability to influence and align cross-functional teams while shaping peers’ work through technical guidance and communication.
• Track record of organizational-wide impact through systems, frameworks, or initiatives spanning multiple teams or functions.
• Proven ability to ship end-to-end ML features from problem framing through deployment and long-term maintenance.
• Production experience with language models, dialog systems, or generative AI.
• Strong foundation in NLP, deep learning, or ML infrastructure best practices.
• Excellent communication skills for representing technical work to leadership and stakeholders.
• Enthusiasm for R&D and advancing applied AI for conversational systems.

Responsibilities

• Lead the end-to-end delivery of multiple machine learning initiatives from planning and design through rollout, documentation, and long-term maintenance.
• Partner with risk, product, engineering, design, and operations leaders to define and execute long-term ML roadmaps.
• Guide team direction, identify ML and AI opportunities, and advise leadership on strategic tradeoffs.
• Drive R&D on chatbot architectures using LLMs, RAG, fine-tuning, and real-time inference.
• Design, deploy, and maintain ML models for conversational agents and support chatbots across Block products.
• Develop ML-powered agent tools and real-time recommendation systems to improve support effectiveness and customer outcomes.
• Represent the team’s systems and programs to stakeholders, cross-functional partners, and external audiences.

Job description

• Lead the end-to-end delivery of multiple machine learning initiatives from planning and design through rollout, documentation, and long-term maintenance.
• Partner with risk, product, engineering, design, and operations leaders to define and execute long-term ML roadmaps.
• Guide team direction, identify ML and AI opportunities, and advise leadership on strategic tradeoffs.
• Drive R&D on chatbot architectures using LLMs, RAG, fine-tuning, and real-time inference.
• Design, deploy, and maintain ML models for conversational agents and support chatbots across Block products.
• Develop ML-powered agent tools and real-time recommendation systems to improve support effectiveness and customer outcomes.
• Represent the team’s systems and programs to stakeholders, cross-functional partners, and external audiences.

Responsibilities

• Lead the end-to-end delivery of multiple machine learning initiatives from planning and design through rollout, documentation, and long-term maintenance.
• Partner with risk, product, engineering, design, and operations leaders to define and execute long-term ML roadmaps.
• Guide team direction, identify ML and AI opportunities, and advise leadership on strategic tradeoffs.
• Drive R&D on chatbot architectures using LLMs, RAG, fine-tuning, and real-time inference.
• Design, deploy, and maintain ML models for conversational agents and support chatbots across Block products.
• Develop ML-powered agent tools and real-time recommendation systems to improve support effectiveness and customer outcomes.
• Represent the team’s systems and programs to stakeholders, cross-functional partners, and external audiences.

Requirements

• 10+ years of experience in machine learning, applied AI, or product ML, with deep technical expertise.
• Demonstrated ability to influence and align cross-functional teams while shaping peers’ work through technical guidance and communication.
• Track record of organizational-wide impact through systems, frameworks, or initiatives spanning multiple teams or functions.
• Proven ability to ship end-to-end ML features from problem framing through deployment and long-term maintenance.
• Production experience with language models, dialog systems, or generative AI.
• Strong foundation in NLP, deep learning, or ML infrastructure best practices.
• Excellent communication skills for representing technical work to leadership and stakeholders.
• Enthusiasm for R&D and advancing applied AI for conversational systems.

Benefits

• Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning benefits are offered.
• Compensation varies by location and is organized into four U.S. labor-market zones.
• The company provides an inclusive interview experience and reasonable accommodations for disabled applicants.