Job Description
Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise.
Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members.
Members of this team will:
Develop Archer’s multi-disciplinary optimization (MDO) engine, workflows, and high performance computing resources for aircraft concept development
Translate business goals and use cases into optimization objectives and constraints.
Deploy the MDO engine to create optimal vehicle designs for use cases.
Communicate findings to stakeholders and support executive decision making.
Support systems engineers to transform their designs into high level requirements, and the broader Archer engineering team to turn it into reality.
Team Skills
Members of this team bring one or more of the following capabilities and past experiences:
General aircraft concept design
Development of Analysis of Advanced Air Mobility (AAM) network simulations and evaluation of fleet performance
Design of eVTOL mission profiles, assessment of vehicle performance, identification of load cases
Understanding of eVTOL vehicle control algorithms.
Physics-based and semi-empirical modeling of electric powertrains; sizing of electrical powertrains.
Coupled aerodynamic and structural modeling and optimization of fuselage, wing, and propeller via both high-fidelity (i.e. CFD, FEA) and reduced-order methods.
Development of physics-based mass and cost estimation relationships (CERs) for aerospace components.
Surrogate modeling via Neural Networks or Gaussian Processes (Kriging) for use as fast-running model proxies.
Modeling complex multi-physics systems of ODEs and DAEs and solving them using numerical methods.
Gradient-based optimization, including Automatic Differentiation and Adjoint methods.
Direct collocation and simultaneous sizing/trajectory optimization.
Evolutionary algorithms and/or other non-gradient based methods for discrete-variable optimization.
Uncertainty Quantification (UQ) and sensitivity analysis methods.
Deploying parallelized simulation, analysis, or optimization workflows on cloud infrastructure and systems to store, query, and handle the resultant large datasets.
Collaborating with discipline experts to build accurate models and validate analysis and optimization results
Communicating complex technical topics and driving consensus amongst both technical and non-technical stakeholders
Candidate Requirements
We are currently open to hiring for this position at the Senior, Staff, or Senior Staff level. Your final leveling and base salary will be determined by interview calibration and a comprehensive assessment of your skills and experience.
Senior Level: 5+ years of relevant engineering experience.
Base Salary Range: $130,000 - $160,000
Staff Level: 8+ years of relevant engineering experience, including a proven track record of architectural ownership and technical leadership.
Base Salary Range: $160,000 - $200,000
Senior Staff Level: 12+ years of relevant engineering experience, with a history of driving multi-year technical strategy and cross-organizational impact.
Base Salary Range: $200,000 - $240,000
Additional Compensation: The base salary ranges listed above do not include our total rewards package. The final bonus and equity amounts will be determined during the interview calibration process.
Proficient in Python with NumPy, SciPy, OpenMDAO, JAX, CasADi, SMT, PyTorch, and / or other specialized scientific and optimizati ... (truncated, view full listing at source)