Senior AI/ML Engineer - Generative AI for Software Development

GE Aerospace•Grand Rapids, MI

6d•$130,000 - $173,000•Onsite

About The Position

GE Aerospace Defense & Systems is seeking a Senior AI/ML Engineer to join its Emerging Technologies team in Grand Rapids, Michigan. The role focuses on applying large language models and generative AI across the software development lifecycle for mission-critical avionics and defense systems. The engineer will help build secure, trustworthy, and practical AI-enabled tools to improve code authoring, test generation, requirements verification, change review, and technical documentation. The role combines software engineering and machine learning expertise with hands-on development of LLM-powered applications. It involves building and deploying tools and workflows, integrating AI into engineering toolchains and developer processes, and optimizing solutions for secure, on-premises, air-gapped, and classified environments. The engineer will establish evaluation methods and guardrails to support accuracy, security, reliability, usability, software assurance, traceability, and human accountability in certified software environments. The engineer will collaborate with software, systems, test, cybersecurity, and business teams to identify valuable use cases and transition solutions into broader engineering adoption. The role also includes mentoring others, sharing practices, and helping define how GE Aerospace scales generative AI in engineering. The position is onsite in Grand Rapids, Michigan, and relocation assistance is provided. It requires an active security clearance and the ability to maintain a U.S. Government Security Clearance; U.S. citizenship is stated as a prerequisite for clearance. The role also requires access to U.S. export-controlled information, with employment contingent on proving eligible U.S. Person status.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or a related STEM field.
At least 5 years of experience in software engineering, machine learning engineering, or a closely related technical field.
Hands-on experience developing software solutions in production or operational environments.
Active Security Clearance.
Ability to maintain a U.S. Government Security Clearance; the posting states U.S. citizenship is a prerequisite for a security clearance.
Willingness to work onsite in Grand Rapids, Michigan.
Ability to prove eligible U.S. Person status for access to U.S. export-controlled information.

Nice To Haves

Master’s degree in Computer Science, Machine Learning, or a related field.
Experience building and deploying LLM-based applications such as RAG systems, AI coding assistants, copilots, or agent-based workflows.
Strong Python programming skills and experience with modern ML/LLM frameworks such as PyTorch, Hugging Face Transformers, LangChain, or LlamaIndex.
Working knowledge of C/C++ and embedded software development environments.
Experience with vector databases, embeddings, and search technologies.
Familiarity with fine-tuning, quantization, and efficient inference serving for production-scale LLM systems.
Experience integrating AI capabilities into DevSecOps and software engineering workflows.
Background in aerospace, defense, medical, automotive, or other mission-critical industries.
Familiarity with software assurance or certification considerations such as DO-178C, MISRA, or CERT C/C++.
Knowledge of AI security, data governance, and responsible AI practices.
Experience deploying solutions in secure, disconnected, or classified environments.
Strong problem-solving, communication, and collaboration skills.

Responsibilities

Design, build, and deploy LLM-powered tools for code generation, code review, debugging, refactoring, automated test creation, and documentation.
Develop retrieval-augmented generation (RAG) pipelines grounded in internal engineering artifacts, including codebases, requirements, design documentation, standards, and domain knowledge.
Create agentic workflows that interact with engineering toolchains such as compilers, static analyzers, test frameworks, version control systems, and issue-tracking platforms.
Evaluate and select models based on performance, cost, latency, licensing, and security requirements.
Apply prompt engineering, fine-tuning, and parameter-efficient adaptation to improve model usefulness for aerospace and embedded software use cases.
Optimize model deployment for secure, on-premises, air-gapped, and classified environments.
Integrate AI capabilities into developer workflows, including IDE experiences, CI/CD pipelines, merge-request checks, and software quality processes.
Establish evaluation methods, benchmarks, and guardrails to measure and improve accuracy, security, reliability, and usability.
Help ensure AI-assisted outputs support software assurance, traceability, and human accountability in certified software environments.
Partner with software, systems, test, cybersecurity, and business teams to identify high-value use cases and transition solutions into broader engineering adoption.
Mentor others, share best practices, and help define how GE Aerospace scales generative AI in engineering.

Benefits

Medical, dental, vision, and prescription drug coverage.
Access to a Health Coach from GE Aerospace.
Employee Assistance Program providing confidential assessment, counseling, and referral services.
GE Aerospace Retirement Savings Plan, including 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.
Annual discretionary bonus based on a percentage of base salary or commission based on the plan.
Professional development and competitive compensation.
Corporate relocation assistance.