Asks for

The ad says“Gradient-based optimization, including Automatic Differentiation and Adjoint methods.”
The ad says“Development of Analysis of Advanced Air Mobility (AAM) network simulations and evaluation of fleet performance”
The ad says“Coupled aerodynamic and structural modeling and optimization of fuselage, wing, and propeller via both high-fidelity (i.e. CFD, FEA) and reduced-order methods.”
The ad says“General aircraft concept design”
The ad says“Gradient-based optimization, including Automatic Differentiation and Adjoint methods.”
The ad says“Proficient in Python with NumPy, SciPy, OpenMDAO, JAX, CasADi, SMT, PyTorch, and / or other specialized scientific and optimization packages.”
The ad says“Coupled aerodynamic and structural modeling and optimization of fuselage, wing, and propeller via both high-fidelity (i.e. CFD, FEA) and reduced-order methods.”
The ad says“Direct collocation and simultaneous sizing/trajectory optimization.”
The ad says“Physics-based and semi-empirical modeling of electric powertrains; sizing of electrical powertrains.”
The ad says“Evolutionary algorithms and/or other non-gradient based methods for discrete-variable optimization.”
The ad says“Design of eVTOL mission profiles, assessment of vehicle performance, identification of load cases”
The ad says“Understanding of eVTOL vehicle control algorithms.”
The ad says“Coupled aerodynamic and structural modeling and optimization of fuselage, wing, and propeller via both high-fidelity (i.e. CFD, FEA) and reduced-order methods.”
The ad says“Surrogate modeling via Neural Networks or Gaussian Processes (Kriging) for use as fast-running model proxies.”
The ad says“Gradient-based optimization, including Automatic Differentiation and Adjoint methods.”
The ad says“Proficient in Python with NumPy, SciPy, OpenMDAO, JAX, CasADi, SMT, PyTorch, and / or other specialized scientific and optimization packages.”
The ad says“Surrogate modeling via Neural Networks or Gaussian Processes (Kriging) for use as fast-running model proxies.”
The ad says“Development of physics-based mass and cost estimation relationships (CERs) for aerospace components.”
The ad says“Surrogate modeling via Neural Networks or Gaussian Processes (Kriging) for use as fast-running model proxies.”
The ad says“Modeling complex multi-physics systems of ODEs and DAEs and solving them using numerical methods.”
The ad says“Proficient in Python with NumPy, SciPy, OpenMDAO, JAX, CasADi, SMT, PyTorch, and / or other specialized scientific and optimization packages.”
The ad says“Proficient in Python with NumPy, SciPy, OpenMDAO, JAX, CasADi, SMT, PyTorch, and / or other specialized scientific and optimization packages.”
The ad says“Proficient in Python with NumPy, SciPy, OpenMDAO, JAX, CasADi, SMT, PyTorch, and / or other specialized scientific and optimization packages.”
The ad says“Proficient in Python with NumPy, SciPy, OpenMDAO, JAX, CasADi, SMT, PyTorch, and / or other specialized scientific and optimization packages.”
The ad says“Proficient in Python with NumPy, SciPy, OpenMDAO, JAX, CasADi, SMT, PyTorch, and / or other specialized scientific and optimization packages.”
The ad says“Uncertainty Quantification (UQ) and sensitivity analysis methods.”
The ad says“Proficient in Python with NumPy, SciPy, OpenMDAO, JAX, CasADi, SMT, PyTorch, and / or other specialized scientific and optimization packages.”
The ad says“Surrogate modeling via Neural Networks or Gaussian Processes (Kriging) for use as fast-running model proxies.”
The ad says“Uncertainty Quantification (UQ) and sensitivity analysis methods.”

Headquartered in Silicon Valley, California, Archer is a leader in the next-gen aerospace sector building an end-to-end advanced air mobility platform that delivers air taxis, unmanned aircraft systems (“UAS”), aviation-related physical artificial intelligence (“AI”) solutions, and other technologies to customers worldwide across the commercial aerospace and defense sectors.

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.

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.

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

Information collected and processed as part of any job applications you choose to submit is subject to Archer's Candidate Privacy Policy.

Certain positions may be eligible for visa sponsorship.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

Archer Aviation does not engage with external recruiting agencies/individual recruiters with whom it does not have a prior written agreement. Archer reserves the right to make use of any unsolicited resumes that it receives and bears no responsibility for payment of any fees asserted from the use of unsolicited resumes. If you are a recruiting agency or individual recruiter wishing to do business with Archer, please reach out to People@archer.com. All employment processes are managed by the Archer People Team.