PhD-resident will design, fabricate, and characterize electrochemical sensors (pA–nA range), develop potentiostat/A FE hardware and firmware, run rigorous experiments, integrate sensors with microfluidic wearables, and analyze transient current data to inform hardware roadmaps.

Design, build, and deploy production-grade AI systems for supply chain applications. Prototype and productionize LLM and Foundation Model solutions, integrate AI with enterprise systems (ERP, cloud, Kubernetes/Terraform), lead technical decisions, mentor teams, and ensure responsible, safe AI deployment and operations.

This role focuses on applying Vision-Language Models to enhance understanding of electrical infrastructure. Responsibilities include dataset curation, model evaluation, and collaboration with research scientists.

The role involves developing advanced simulation and optimization tools, collaborating with experts, and leveraging modern computing for grid computations.

Support testing and characterization of revolutionary nanodevices, analyze data, engage in cross-functional teams, and contribute to experimental setups.

Join a multidisciplinary team to build and deploy machine learning models to address challenges in the electric grid, operationalizing ML at scale.

The Rapid Evaluator role involves assessing and developing breakthrough technology ideas, leading technical teams, and refining proposals for global impact.

As Head of Product Design, you'll lead the design team, define strategic direction, create design systems, and prototype AI-driven solutions for complex energy systems.

Lead the development of internal tools for engineering productivity, focusing on platform strategy, CI/CD modernization, and agentic AI adoption.

Tapestry seeks passionate individuals for future roles in engineering, operations, and energy systems, focusing on clean energy and innovation.

The role involves collaborating on machine learning and reinforcement learning projects, developing algorithms, engaging with the research community, and prototyping RL solutions. PhD candidates in STEM fields are preferred.

Design and implement advanced AI systems to optimize industrial processes by creating structured knowledge graphs from unstructured data, focusing on complex reasoning with AI models.

Translate multi-modal AI research into 0-1 products: design and run ML experiments, build scalable training and evaluation infrastructure, implement MLOps and data pipelines, deploy models, and use AI code tooling to move experiments to production MVPs.

This role involves leading innovation projects at X, developing breakthrough technologies from inception to product launch, and creating external partnerships.

The Rapid Evaluator will identify and assess potential technology-enabled projects, lead teams, and develop business concepts for revolutionary technologies. Requires critical thinking and experience in breakthrough tech.

Lead and organize early-stage geoscience AI initiatives: coordinate workstreams, manage partners, define metrics, run experiments, document progress, and act as the GM proxy to remove roadblocks and scale prototypes into products.

Provide commercial, product, and employment legal advice across moonshot projects: draft and negotiate complex agreements, counsel on IP/privacy/data security and AI/ML issues, advise HR on labor compliance and personnel matters, manage disputes and investigations, supervise outside counsel, and improve legal processes to enable scaling and commercialization.

Design, architect, and deploy AI systems. Develop production-grade software, lead technical initiatives, and ensure responsible AI development while mentoring teams in a fast-paced environment.

As a Backend Software Engineer at Tapestry, you'll design and implement scalable infrastructure for AI-driven energy solutions, collaborate with cross-functional teams, and interface with external partners to refine technical requirements.

As a Product Lead for the Data Platform at Tapestry, you will create a scalable, secure, and user-centric platform for energy data, ensuring compliance and privacy while enabling cross-functional insights and collaboration among product teams and partners.