Arcturus

Arcturus

Lead Process Engineer

Los Angeles · Exec

Sponsorship not specifiedDetected 83 days ago
Data AnalysisStatisticsA/B TestingIntellectual PropertyCadenceRoboticsMechanical DesignLeadershipWriting

About the role

  • Translate early technical learnings into repeatable process recipes, standard work, process flow diagrams, and controlled operating procedures
  • Define critical process parameters and critical quality attributes across each step of the conductor manufacturing flow
  • Establish pragmatic process controls that preserve electrical conductivity, thermal performance, mechanical integrity, and nanomaterial stability

Responsibilities

  • Our technology is designed to significantly improve the performance of electric motors for drones and robotics, heat sinks, and ultimately the entire energy grid.
  • At its core, Arcturus is developing a new class of carbon nanomaterial-infused metal matrix composites for high-performance conductor applications.
  • This is a ground-floor opportunity to help build something that has never been done before.
  • As the founding process engineer, you'll work directly with the founder/CEO to shape the technical direction of the company, translate scientific insight into real product performance, and help build a category-defining materials platform from scratch.
  • This is a hands-on leadership role spanning feedstock preparation, build recipes, carbon infusion or growth steps, post-processing, QA controls, documentation, and pilot readiness.
  • Own Arcturus' R&D-to-pilot process flow, from feedstock handling and preparation through LPBF/DED processing, carbon infusion or growth steps, post-processing, finishing, inspection, and sample release
  • Partner with additive manufacturing and nanomaterials leads to ensure each process step is technically sound, measurable, and scalable
  • Build and run a disciplined design of experiments (DOE) cadence to expand process windows, improve repeatability, increase yield, and reduce cycle time
  • Develop process maps that connect feedstock, atmosphere, laser parameters, thermal history, growth or infusion conditions, and post-processing to final material performance
  • Identify bottlenecks, failure modes, and sources of variation, then drive practical solutions that improve consistency and throughput

Requirements

  • 8+ years of hands-on process engineering, manufacturing engineering, materials processing, or advanced process development experience
  • Strong understanding of process-structure-property relationships in metals, metal matrix composites, or other high-performance material systems
  • Experience using DOE, statistical analysis, process controls, and structured root-cause methods to improve yield, repeatability, and performance

Nice to have

  • Experience with LPBF, DED, laser processing, welding, CVD/LCVD/LACVD, high-temperature gas processes, or related advanced manufacturing methods
  • Experience with aluminum, copper, conductor materials, or metal matrix composites
  • Direct experience with carbon nanomaterial-metal composites, covetics, graphene, carbon nanotubes, or carbon-metal interface engineering
  • Familiarity with conductor, cable, automotive, aerospace, energy, or utility qualification pathways
  • Experience working in a startup or fast-paced R&D-to-manufacturing environment
  • Scientific ownership with direct product impact
  • The chance to define the playbook for nanomaterial-enhanced conductors
  • Visa sponsorship for highly qualified candidates (H-1B transfers, F-1, or STEM OTP)

Compensation

  • Competitive cash compensation and meaningful equity

Benefits

  • Competitive cash compensation and meaningful equity

Company info

  • We are seeking a Lead Processing Engineer who can own the end-to-end process flow that turns early prototypes into reliable, repeatable, and scalable conductor products.

Visa & Work Authorization

  • Visa sponsorship for highly qualified candidates (H-1B transfers, F-1, or STEM OTP)

This listing is sourced directly from Arcturus's careers page and normalized into a canonical job model.