Manufacturing Intelligence Engineer

Location: Palo Alto, CA

Department: Business

Location Type: HYBRID

Employment Type: FULL_TIME

• You have hands-on experience in electronics or semiconductor manufacturing — whether in failure analysis, test engineering, process engineering, quality, hardware development, or a similar technical role.
• You're comfortable working with messy, real-world manufacturing data to identify patterns, form hypotheses, and determine what evidence is needed before recommending action.
• You know how to investigate root cause across production data, test data, supply chain data, process history, product context, and customer-reported symptoms.
• You don't stop at analysis — you drive corrective actions and can demonstrate measurable impact on yield, failure analysis cycle time, throughput, scrap/rework, or bonepile recovery.
• You communicate complex technical findings clearly to diverse audiences: engineering teams, OEM/CSP stakeholders, manufacturing operators, and internal teammates.
• You're excited to work with next-generation AI tools and apply rigorous engineering judgment to AI-generated findings.
• You're product-minded — you can spot workflow friction, identify product gaps, and recognize repeatable customer use cases while staying focused on delivering outcomes.
• You thrive in ambiguity, take ownership without waiting for perfect instructions, and are energized by solving hard technical problems with real customer stakes.

• Own customer investigations using Instrumental Solve, turning ambiguous manufacturing questions into structured analyses, validated findings, and recommended next steps.
• Work directly with customer engineering teams, OEMs, CSPs, and manufacturing stakeholders to investigate issues impacting yield, throughput, failure analysis time, bonepile recovery, scrap/rework, or time-to-market.
• Use manufacturing data across production, test, supply chain, environment, product, logs, and customer-reported issues to identify patterns, form hypotheses, and pressure-test likely root causes.
• Drive corrective actions with customer teams and manufacturing sites, ensuring findings lead to real changes in process, product, supplier, or operational behavior — building credibility and driving sustained Solve adoption along the way.
• Quantify the impact of Solve investigations by connecting actions taken to measurable improvements in customer manufacturing metrics.
• Partner closely with Instrumental Product and Engineering to identify product gaps, repeatable use cases, and workflow improvements that make Solve more valuable across customers.
• Help define how Instrumental delivers Solve outcomes as the product scales, including investigation playbooks, customer workflows, and best practices for closing the loop from insight to impact.