Advanced Lead Scientist – MBSE & Formal Methods – GE Aerospace Research at GE Aerospace | NY, US | Rezi

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

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

GE Aerospace · NY, US

2 weeks ago

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

GE Aerospace · NY, US

17 days ago
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About the Role

As an Advanced Lead Scientist in the Knowledge Discovery & High Assurance Systems Laboratory, you will 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. You will design and develop technologies that enable efficient system model development, improve requirement quality and traceability, and verify system behavior using mathematically rigorous methods and Artificial Intelligence (AI).

Responsibilities

  • Contribute to, and in some instances, lead innovative research projects in the Aerospace domain that define and implement software tools to improve the development of software and systems including advanced technologies for integrated modeling, simulation, and verification.
  • 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.

Requirements

  • 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 Python and code repositories such as Git.
  • Demonstrated track record of very high technical competence that includes strong coding skills and individual technical accomplishments.
  • Proven teamwork skills.
  • Strong written and verbal communication skills.
  • Legal authorization to work in the U.S. is required.
  • Must be willing to work out of an office located in Niskayuna, NY.
  • Must be 18 years or older.
  • Ability to communicate ideas in both technical and user-friendly language.
  • Entrepreneurial drive and a demonstrated ability to achieve goals in an innovative and fast-paced environment.
  • Requires access to U.S. export-controlled information; employment contingent upon ability to prove status as a U.S. Person (U.S. lawful permanent resident, U.S. Citizen, asylee or refugee status).

Skills

  • Formal Methods
  • Model-Based Systems Engineering (MBSE)
  • Large Language Models (LLMs)
  • High Assurance Systems
  • AI
  • Python
  • Git

Location

  • Niskayuna, New York

Work Type

  • Onsite

Experience Level

  • Advanced Lead Scientist
  • Advanced Lead Engineer

Education Level

  • PhD in Electrical, Control or Computer Engineering or related discipline
  • Master’s degree in Electrical, Control or Computer Engineering or related discipline

Salary/Compensations

  • $112,000 - $186,000 USD Annually
  • Eligible for an annual discretionary bonus

Benefits

  • Comprehensive benefits and programs to support health and wellbeing.
  • Healthcare benefits include medical, dental, vision, and prescription drug coverage.
  • Access to a Health Coach from GE Aerospace.
  • Employee Assistance Program.
  • Retirement benefits include the GE Aerospace Retirement Savings Plan, a 401(k) savings plan with company matching contributions and company retirement contributions.
  • Access to Fidelity resources and planning consultants.
  • Tuition assistance.
  • Adoption assistance.
  • Paid parental leave.
  • Disability insurance.
  • Life insurance.
  • Paid time-off for vacation or illness.
  • Relocation Assistance Provided: Yes

About the Company

  • 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.
  • We invent the future of flight, lift people up, and bring them home safely.
  • GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation.

Equal Opportunity

  • GE Aerospace is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
  • GE Aerospace will only employ those who are legally authorized to work in the United States for this opening.
  • Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
  • Employees may also be subject to random and reasonable-suspicion drug and alcohol testing.