Build zero-to-one AI infrastructure and workflows that help hardware engineers investigate anomalies, perform root-cause analysis, and reason over telemetry, time series, logs, and other engineering data. The role requires production AI experience, strong backend or distributed-systems fundamentals, and comfort working directly with customers.
Salary not listed
On-siteFullstack Engineering
About the role
Responsibilities
Build systems powering Hardware Intelligence, including agent infrastructure, evaluation pipelines, retrieval systems, and tooling for reasoning over engineering data.
Design and ship AI-powered workflows that help engineers investigate anomalies, perform root-cause analysis, and understand complex hardware behavior.
Work across large-scale time series, telemetry, logs, and other engineering datasets to build robust, production-ready systems.
Prototype new approaches quickly, evaluate them with customers, and iterate based on real-world feedback.
Partner with engineers and product leaders to determine where the team should invest next.
Establish engineering patterns, infrastructure, and best practices as Hardware Intelligence scales.
Engage directly with customers to understand complex engineering workflows and translate them into product capabilities.
Requirements
Experience building AI or machine-learning products shipped to production.
Experience with large datasets, time series data, observability platforms, data infrastructure, or machine-learning systems.
Background in ML, data science, applied AI, or an adjacent field involving data-intensive systems.
Strong software engineering fundamentals and experience designing scalable backend or distributed systems.
Experience taking products from zero to one, at a startup or within an entrepreneurial team.
Strong product instincts and curiosity about customer problems.
Nice to Have
Experience with telemetry, sensors, robotics, aerospace, industrial systems, autonomous systems, or other hardware domains.
Experience building agentic systems, LLM applications, retrieval pipelines, or evaluation infrastructure.
Familiarity with time series databases, observability tooling, or data platforms.
Experience supporting engineers or scientists working with large-scale operational data.
Prior startup founding experience or experience on an incubation or new-products team.
Compensation & Benefits
100% coverage of medical, dental, and vision insurance.
Unlimited PTO and sick leave.
Free lunch, snacks, and coffee.
Professional development stipend.
Annual company retreat.
ITAR-related work may require U.S. citizenship or nationality, lawful permanent residency, refugee or asylee status, or eligibility to obtain required authorizations.
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