Staff Machine Learning Engineer, Modeling, Support
Lead end-to-end delivery of ML initiatives for customer support, focusing on conversational AI and generative AI. Partner with cross-functional teams to define ML roadmaps and drive R&D efforts for next-generation chatbot architectures.
About the job
The Role
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.
You Will
- 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
You Have
- 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
Technologies We Use and Teach
- Python, PyTorch, TensorFlow, or JAX
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.
Skills
Machine Learning, Generative AI, NLP, Deep Learning, Python, PyTorch, TensorFlow, JAX, Language Models, Dialog Systems
Similar jobs
ML Engineering jobs
Grafana Labs
United StatesBuilds and owns production multi-agent AI infrastructure, backend integrations, and workflow automation for marketing operations. Requires 8+ years of software engineering experience, strong Python and JavaScript/Node.js skills, production LLM experience, and deep Google Cloud expertise.
OnePay
United States
Design and productionize ML, deep learning, and LLM models for personalization, recommendations, and search systems. Requires 7+ years building production ML/AI with business impact and strong cross-functional collaboration skills.
Talkiatry
United States
Staff-level engineer responsible for building AI agents and automation, evaluating developer AI tools, and driving adoption across the engineering organization. Requires 8+ years of software engineering experience plus production experience with LLMs, agentic systems, and applied machine learning.
Aleph
United States
Own the shared AI foundation powering Aleph’s financial planning products, including model routing, context and tool systems, evaluations, and observability. The role requires Staff-level experience shipping production LLM and agentic systems, strong technical judgment, and a pragmatic builder’s mindset.
Nuro
Mountain View, CA
Develop and productize online mapping models for autonomous navigation using real-world sensor data. The role requires deep ML expertise, robotics or computer vision experience, strong Python and deep learning framework skills, and a staff-level ability to deliver practical solutions.