Block
Staff Machine Learning Engineer (Modeling), Support
Rol remoto de 11003 Risk - Prod Dev - Square con fit claro de ubicación del candidato.
PublicadoAgregado recientemente
Países elegibles27 países aceptados
Señal de seniorityLead
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Resumen del rol
Staff Machine Learning Engineer (Modeling), Support
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
Details
- 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
- 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
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