Imagine a piloted air taxi that takes off vertically, then quietly carries you and your fellow passengers over the congested city streets below, enabling you to spend more time with the people and places that matter most. At Joby, we've been working to make that dream a reality since 2009 and we're now in the final stages of certifying our aircraft with the FAA. With plans to launch our aircraft in the US and Dubai, we're now scaling manufacturing and preparing for the launch of our commercial service.

Joby Aviation is seeking a passionate & experienced thermal engineer to join our Powertrain team in San Carlos, CA to support development of the Joby S4 aircraft.  In addition to building & verifying simulations, as thermal attribute owners we bring cross-functional teams together to highlight sensitivities, inform trade studies, and drive optimal designs.  This role will primarily support the Electric Propulsion Unit, Energy Storage & Distribution System, System Electronics, & Electrical System Installation teams.

• Determine appropriate modeling complexity to support critical designs, program decisions, & project timelines
• Build & validate models supporting system optimization, performance, & trade studies
• Connect with key stakeholders & function groups together to drive solutions to complex problems
• Build coalitions with key stakeholders & functional groups to drive solutions to completion

• Experience with product design cycle & managing project deliverables
• Strong fundamentals in thermodynamics, aerodynamics, & data analysis
• Direct experience building lumped-parameter thermal network models
• Working knowledge of at least one CFD analysis toolkit such as STAR-CCM, OpenFOAM, Ansys, etc.
• Familiarity with at least one scripting language or optimization toolkit
• 3+ years of industry experience & post-graduate degree, or demonstrated equivalent

• 5+ years experience with STAR-CCM and 3DX (CATIA)
• Proficiency in Python, Matlab, & Simulink.  Experience with Databricks. 
• Competence in R-value tuning, RMSE minimization, Bayesian optimization, thermal neural networks, & posterior probability sensitivity analysis
• Background in fan impeller design, aeroacoustics modeling, or refrigeration/thermal system control design