Join a company that's reintroducing itself to the aviation community we've helped advance for more than a century. At Honeywell Aerospace (NASDAQ: HONA), we're launching as an independent, publicly traded aerospace and defense company built on a legacy of operational excellence and mission-focused execution.
Our new brand identity pairs that heritage with real momentum, as we build technology that helps pilots navigate with confidence, aircraft operate more efficiently, and operators stay ahead of change. With our systems on board 90% of the world's aircraft, your work here has reach that's rare to find anywhere else.
Focusing on our customers, investing in innovation, and building a culture of accountability and performance is how we're shaping what comes next.
Every horizon. Every mission. Every day.
Honeywell Aerospace products and services are found on aircraft across commercial aviation, defense and space — from engines and cockpit electronics to cabin systems, mechanical components and connectivity solutions. Our technology helps operators fly more safely, reduce fuel consumption, improve on-time performance and deliver a better experience for the people on board.
As aviation continues to evolve, we're also developing systems to support autonomous and supersonic platforms, bringing the same focus on safety and efficiency to the next era of flight. With approximately 36,000 employees worldwide and net sales of $17.4B in 2025, Honeywell Aerospace is one of the largest dedicated aerospace companies in the world. Explore our businesses: https://www.honeywellaerospace.com
We are seeking an AI/ML Engineer with strong fundamentals in mechanical design, computational fluid dynamics, and structural analysis to join the Aerospace Advanced & Applied Technology group. In this role, you will apply machine learning, physics-informed modeling, surrogate modeling, automation, and data-driven engineering methods to accelerate design exploration, simulation workflows, and product technology development for aircraft propulsion engines, power systems, and related components. You will work closely with product architects, simulation specialists, product managers, and Chief Engineers to develop reliable AI-enabled engineering solutions that improve speed, accuracy, and decision-making across mechanical design, CFD, and FEA workflows.
Responsibilities
Qualifications and Experience:
- Master’s degree in mechanical engineering, aerospace engineering or related discipline from a reputed university.
- Strong fundamentals in fluid mechanics, thermodynamics, heat transfer, turbomachinery, solid mechanics, finite element methods, numerical methods, and engineering statistics.
- Good understanding of gas turbine engine components, aerospace mechanical systems, and simulation-driven product development.
- Hands-on exposure to CFD, FEA, or mechanical design workflows, including pre-processing, solver execution, post-processing, and interpretation of simulation results.
- Ability to build and validate AI/ML models using engineering simulation data, experimental data, or operational data for design prediction, optimization, classification, anomaly detection, or reduced-order modeling.
- Experience in physics-informed machine learning, surrogate modeling, response surface modeling, reduced-order models, uncertainty quantification, or optimization for engineering applications.
- Working knowledge of Python-based AI/ML development using libraries such as NumPy, pandas, scikit-learn, TensorFlow, PyTorch, or equivalent platforms.
- Ability to automate engineering workflows for geometry handling, mesh generation, solver setup, data extraction, post-processing, and report generation.
- Capability to interpret CFD and structural analysis results, identify key design drivers, and recommend suitable design changes based on simulation and AI/ML insights.
- Exposure to design of experiments, sensitivity studies, parametric analysis, optimization techniques, and statistical validation of model predictions.
- Proven ability to develop new design concepts and translate data-driven insights into practical engineering recommendations.
- Experience in working with geographically distributed stakeholders and cross-functional engineering teams.
- Innovative mindset with curiosity and initiative to adopt emerging AI/ML trends for aerospace design, simulation, and product technology insertion.
- Strong problem-solving skills, attention to detail, ownership mindset, and ability to manage multiple technical tasks.
- Good communication, presentation, interpersonal, and networking skills.
Qualifications
Desired Skills:
- Programming experience in Python; exposure to MATLAB, C++, JavaScript, or other engineering automation platforms is an added advantage.
- Previous project experience implementing AI/ML methods in the mechanical engineering domain is preferred.
- Knowledge of machine learning methods such as regression, classification, neural networks, variational autoencoders, Gaussian processes, Bayesian optimization, graph neural networks, or reinforcement learning for engineering applications.
- Experience with CAD tools such as NX, Creo, CATIA, or equivalent mechanical design platforms. Exposure to commercial CFD software (Fluent, Star CCM+ etc.)
- Exposure to physics-informed neural networks, neural operators, surrogate models, reduced-order models, digital twins, or AI-assisted solver acceleration for CFD and structural analysis.
- Experience handling simulation datasets, including feature engineering, model training, validation, error analysis, and deployment of reusable AI/ML workflows.
- Familiarity with version control, engineering data management, cloud/HPC environments, and collaborative software development practices.
- Strong oral and written communication skills with the ability to explain AI/ML model behavior, assumptions, limitations, and engineering impact to stakeholders at all levels.
- Ability to collaborate effectively with cross-functional teams and communicate technical outcomes clearly to both engineering and non-engineering stakeholders.
Honeywell Aerospace never requests or accepts money from candidates at any stage of the hiring process. Any demand for payment in exchange for employment opportunities is fraudulent and should be reported immediately to local law enforcement authorities
Skills Required
- Master's degree in mechanical engineering, aerospace engineering or related discipline
- Strong fundamentals in fluid mechanics, thermodynamics, heat transfer, turbomachinery, solid mechanics, finite element methods, numerical methods, and engineering statistics
- Good understanding of gas turbine engine components, aerospace mechanical systems, and simulation-driven product development
- Hands-on exposure to CFD, FEA, or mechanical design workflows including pre-processing, solver execution, post-processing, and interpretation of simulation results
- Ability to build and validate AI/ML models using engineering simulation data, experimental data, or operational data for prediction, optimization, classification, anomaly detection, or reduced-order modeling
- Experience in physics-informed machine learning, surrogate modeling, response surface modeling, reduced-order models, uncertainty quantification, or optimization for engineering applications
- Working knowledge of Python-based AI/ML development using libraries such as NumPy, pandas, scikit-learn, TensorFlow, or PyTorch
- Ability to automate engineering workflows for geometry handling, mesh generation, solver setup, data extraction, post-processing, and report generation
- Capability to interpret CFD and structural analysis results, identify key design drivers, and recommend design changes based on simulation and AI/ML insights
- Exposure to design of experiments, sensitivity studies, parametric analysis, optimization techniques, and statistical validation of model predictions
- Proven ability to develop new design concepts and translate data-driven insights into practical engineering recommendations
- Experience working with geographically distributed stakeholders and cross-functional engineering teams
- Strong problem-solving skills, attention to detail, ownership mindset, and ability to manage multiple technical tasks; good communication and presentation skills
- Exposure to MATLAB, C++, JavaScript and other engineering automation platforms
- Previous project experience implementing AI/ML methods in the mechanical engineering domain
- Knowledge of ML methods such as regression, classification, neural networks, variational autoencoders, Gaussian processes, Bayesian optimization, graph neural networks, or reinforcement learning for engineering applications
- Experience with CAD tools such as NX, Creo, CATIA and commercial CFD software (Fluent, Star CCM+)
- Familiarity with version control, engineering data management, cloud/HPC environments, and collaborative software development practices
The Aerospace Corporation Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The Aerospace Corporation and has not been reviewed or approved by The Aerospace Corporation.
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Retirement Support — The 401(k) plan provides a company‑paid contribution of 8–12% based on years of service with immediate eligibility and vesting, and eligible employees can access retiree medical benefits.
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Leave & Time Off Breadth — Paid time off includes 15 vacation days (rising to 20 after five years), nine paid holidays, and unlimited sick time for exempt employees with accruals for non‑exempt staff.
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Flexible Benefits — Flexible work models include a 9/80 schedule with alternating Fridays off, supported by backup care services, an EAP, relocation assistance, and home‑office stipends where applicable.
The Aerospace Corporation Insights
What We Do
The space enterprise has been transformed by rapid change and growth. New vehicles for national security space, a more rapid launch cadence, proliferated satellite constellations, the pursuit of interplanetary exploration, and thriving commercial ventures are changing the nature of the space industry. The Aerospace Corporation (Aerospace) is a leading architect for U.S. space programs, shaping efforts to outpace threats to our national security while cultivating the technologies needed to further this new era of space commercialization and exploration. Aerospace works across the space enterprise in service of the public interest. In addition to supporting the Department of Defense and the Intelligence Community, our customers include NASA, NOAA, numerous federal agencies, and commercial space — all of whom benefit from our deep technical knowledge. We only pursue business related to the space mission and complementary fields, operating as the nation’s trusted partner to solve the toughest challenges and develop reliable and innovative technologies. Innovation in space occurs when people have the freedom to imagine and do. At Aerospace, we take pride in our readiness to solve some of the most complex challenges in the space enterprise.
Why Work With Us
We are a non-profit corporation chartered by the government to work on the hardest problems in space. We employ technical experts in every discipline of space-related science and engineering who touch every part of the US space program. Come join us as we make an impact bigger than ourselves.
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