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Advanced Lead Scientist – MBSE & Formal Methods – GE Aerospace Research

Job in Town of Niskayuna, Schenectady County, New York, USA
Listing for: Y99000 General Electric Company
Full Time position
Listed on 2026-10-25
Job specializations:
  • Engineering
    Systems Engineer
Salary/Wage Range or Industry Benchmark: 112000 - 186000 USD Yearly USD 112000.00 186000.00 YEAR
Job Description & How to Apply Below
Job Description Summary

Located in Niskayuna, New York, central to the New York Capital District, GE Aerospace Research builds on GE’s 125+ years of industrial research heritage, tackling the most challenging engineering problems through multi-disciplinary teams to deliver innovative technologies. Together, we create and sustain differentiated solutions to maintain competitive advantages for GE Aerospace and our customers. As an Advanced Lead Scientist in the Knowledge Discovery & High Assurance Systems Laboratory, you work individually and in teams to enable multimodal data management, knowledge extraction, knowledge representation and reasoning, scalable computing, full stack software design and development, and formal methods verification and validation of systems.

Job Description

At GE Aerospace Research, we invent the future of flight, lift people up, and bring them home safely. As an Advanced Lead Engineer – High Assurance Systems in the Knowledge Discovery & High Assurance Systems Lab, you will design and develop technologies that enables efficient system model development, improves requirement quality and traceability, and verifies system behavior using mathematically rigorous methods and Artificial Intelligence (AI).

Successful Advanced Lead Engineers will use their expertise in areas of Formal Methods, Model-Based Systems Engineering (MBSE), Large Language Models (LLMs), and High Assurance Systems to perform the following: partner with senior engineers and scientists to collect internal and/or external customer requirements, design and develop novel solutions to demonstrate that safety critical systems are flight worthy, and mentor and guide junior team members to achieve the same.

Essential

Responsibilities
  • You will contribute to, and in some instances, lead innovative research projects in the Aerospace domain that define and implement software tools that improve the development of software and systems including advanced technologies for integrated modeling, simulation, and verification.
  • This will require the successful application of both technical and interpersonal skills.
  • Design and develop tools to model and analyze specifications, systems, and embedded software.
  • Develop technology and tools to verify and trust AI and system models.
  • Develop MBSE practices for complex systems, subsystems, and integrated product architectures.
  • Apply formal methods to improve rigor in requirements analysis, architecture definition, functional correctness, safety, and verification.
  • Establish end-to-end digital thread / traceability across requirements, models, design artifacts, verification evidence, and certification inputs.
  • Evaluate and improve methods, tools, and processes for model integration, simulation, and verification.
  • Provide mentoring and development of staff members in the organization to grow the technical capability and knowledge of the organization with respect to Model-Based Systems Engineering, Formal Methods, and AI technologies.
  • Develop and maintain strategic relationships with internal and external organizations to accelerate and expand the ability to deliver new technology to our business customers.
Required Qualifications
  • PhD in Electrical, Control or Computer Engineering or related discipline, OR Master’s degree in Electrical, Control or Computer Engineering or related discipline with a minimum of 4 years of relevant work experience.
  • Demonstrated core expertise with Formal Methods, Model-Based Systems Engineering, and AI.
  • Experience with embedded software development tools such as Eclipse, CVC4, or Kind 2.
  • Experience with model-based systems engineering tools such as Cameo.
  • Expertise with application and verification of AI algorithms.
  • Expertise in programming languages such as…
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