Summary

Bring first-principles rigor and evidence-backed decisions to deliver production-ready innovations that raise the bar for performance, reliability, and manufacturability. In this role, you will be developing innovative technologies and designs to push the boundaries of safety, comfort, and performance for head protection products. You will lead design maturation by setting performance targets, generating and analyzing data (tests + models), and reducing technical risk to ensure confident launches. You own validation and analysis, turn data into clear decisions, and collaborate across manufacturing, quality, suppliers, and product teams from early exploration through transfer to production.

Key Responsibilities

• Develop innovative solutions that industry leading safety performance in a head protection product.
• Define performance objectives and validation strategies; develop and execute test plans for functional, durability, and environmental requirements.
• Instrument prototypes/fixtures for high-fidelity data capture; analyze results with DOE, regression, and reliability models to quantify trade-offs.
• Collaborate with simulation engineers to develop FEA/CFD/thermal models to lab/field data; update models based on findings; drive root-cause analysis and reliability growth.
• Utilize high speed video, python tools, and other advanced data analysis techniques to synthesize test results into actionable findings
• Partner with manufacturing and suppliers on process capability, materials, and tooling; feed cost/quality/takt insights into design iterations and risk mitigation.
• Plan and execute prototyping—from proof-of-feasibility through production-representative builds—and capture lessons learned to inform downstream development.
• Document technical decisions, assumptions, and test outcomes in clear reports; present findings and recommendations to cross-functional stakeholders.
• Cultivate curiosity toward AI: proactively explore and run small proofs‑of‑concept where machine learning, generative design, and intelligent automation can improve analysis, prototyping, and test design
• Mentor engineers in test design, analysis, and modeling; foster first-principles thinking and measurable outcomes.

Typical Advanced Engineering Workflow

Discovery: Clarify user and business needs; benchmark performance; define success metrics and initial risk hypotheses.

Definition: Translate needs into engineering targets; select validation methods; outline modeling/analysis and prototype plans.

Exploration & Prototyping: Execute tests and simulations; iterate designs; quantify trade-offs; down-select solution paths.

Validation: Confirm performance, reliability, and manufacturability against targets; refine design and process risks.

Transfer to Production: Provide documentation, test methods, critical features/tolerances, and known risks; support ramp as subject-matter expert.

Qualifications

• Bachelor’s degree in Mechanical, Product, or Material Engineering (or related); advanced degree a plus.
• 2+ years experience with energy absorption technologies and/or head protection products
• 5+ years of product development experience in automotive, industrial, consumer/durable goods, or adjacent industries.
• Demonstrated expertise in test planning/execution, data analysis, and modeling/simulation (FEA/CFD/thermal).
• Proficiency in CAD; experience with DFMA, prototyping methods, and supplier collaboration.
• Hands-on with instrumentation/DAQ and statistical tools (e.g., JMP/Minitab); familiarity with reliability methods (e.g., accelerated life testing, Weibull).
• Excellent communication skills—able to synthesize complex data into clear design recommendations; strong cross-functional collaboration.
• Practical experience applying ML/AI to guide mechanical design and integrate proven tools into standard engineering workflows
• Self-starter comfortable learning beyond core discipline; able to manage ambiguous design tasks.
• Willingness to travel ~10% (domestic/international).