We are seeking driven, experienced, and innovative modeling, simulation, and optimization engineers to join our Concept Development team and architect the future of electric flight. Our team develops multi-disciplinary physics simulations, advanced optimization methods, and large-scale cloud computing infrastructure, then deploys these tools to design optimal vehicle configurations. We are exceptionally data-driven and rigorous in all of our methods. We value a strong understanding of the fundamentals of numerical methods and assessments of analysis uncertainties. We are passionate about developing electric flight, and appreciate the opportunity we have in this time and place to steer and accelerate its future.
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
- Proficient in Python with NumPy, SciPy, OpenMDAO, JAX, CasADi, SMT, PyTorch, and / or other specialized scientific and optimization packages.
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.
