Senior Staff Machine Learning Engineer
About The Position
Tapestry, a team within Alphabet originally created at X, is building AI-powered tools for the electricity ecosystem. It works with partners across the U.S., U.K., Chile, New Zealand, Australia, and Brazil to help the energy system become more visible, reliable, affordable, abundant, and clean. The Senior Staff Machine Learning Engineer will be a foundational architect of Tapestry’s multi-year machine learning strategy. The role bridges AI research, the physics of continental-scale power grids, and production ML/AI systems, including multimodal machine learning, agentic systems, and ML/AI operations. The engineer will architect systems to advance grid planning, simulation, and asset intelligence at continental scale.
Requirements
- Master’s degree or PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related quantitative field, or equivalent practical experience.
- 10+ years of professional experience building, training, and deploying large-scale machine learning systems in production.
- Deep proficiency with modern machine learning frameworks such as PyTorch, JAX, or TensorFlow.
- Demonstrated experience architecting systems for massive datasets or highly compute-intensive, parallel workloads.
- Experience collaborating across technical disciplines and functions, aligning stakeholders around complex architectural decisions, and mentoring senior technical leaders.
- Ability to apply first-principles thinking and structured technical judgment to complex, ambiguous problems spanning machine learning, physical systems, and production infrastructure.
- Strong written and verbal communication skills, including the ability to explain complex technical concepts to multidisciplinary audiences.
Nice To Haves
- Experience applying machine learning to physical, interconnected networks.
- 4+ years of professional experience with grid modeling, simulation, state estimation, or power-system optimization, including familiarity with physical grid constraints, utility data structures, or spatiotemporal grid modeling.
- Familiarity with commercial grid-simulation software or numerical solvers such as PSS®E, GridLAB-D, or MATPOWER, alongside scientific Python tools.
- Open-source contributions or peer-reviewed publications at leading AI conferences.
- Experience in a high-growth or rapidly evolving technical environment.
Responsibilities
- Own the technical roadmap and system architecture for Tapestry’s intelligence engines, including systems spanning multimodal machine learning, graph neural networks, geospatial and remote-sensing data, reinforcement learning for physical control systems, and multi-turn agentic systems.
- Partner with machine learning technical leads, power systems scientists, software engineers, product managers, and global utility partners to turn large-scale grid data into actionable insights for grid planning, operations, and maintenance.
- Mentor senior and staff-level engineers, establish rigorous production standards, and align cross-functional stakeholders around architectural direction.
- Advance the use of state-of-the-art AI architectures, including agentic AI, physics-informed ML, natural language understanding, and geospatial intelligence, to address energy-infrastructure challenges in production.
- Establish scalable architectural patterns and technical standards that improve the reliability, performance, and maintainability of machine learning systems.
- Shape long-term machine learning strategy through first-principles thinking, technical analysis, and clear decision-making.
Benefits
- Competitive salary and equity
- Medical, dental, and vision coverage
- Generous PTO
- Flexible hybrid work model
- 401(k) with employer contribution
- Professional development
- Opportunity to work on important real-world problems within an Alphabet-backed environment
- Bonus
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What This Job Offers
Job Type
Full-time
Career Level
Senior
