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About This Role
Job Description Summary
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This position provides IT engineering for the rapid, scalable, and compliant delivery of enterprise software applications and foundational workflows. The hallmark of our team is our ability to build next\-generation applications by leveraging agentic AI development tooling using Claude Code to execute against three core pillars: modernizing our legacy portfolio capabilities by engineering new, operationally stable software alternatives; informing SaaS "make vs. buy" decisions at scale by rapidly prototyping bespoke solutions; and driving enterprise upskilling by establishing blueprint patterns for AI\-assisted application development. These efforts allow for significant operational efficiency and consumption\-focused innovation across GE Aerospace, as well as provide for improved, cutting\-edge software services to our global workforce and customers.Job Description
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### Roles and Responsibilities
In this role, you will:
- Architect and design sound/supportable technical solutions for net\-new software applications built from the ground up utilizing Claude Code and agentic workflows
- Evaluate legacy systems to determine capabilities and requirements necessary to build high\-performance, operationally stable replacement applications using generative development tools
- Code complex, integrated, and modular applications by actively using Claude Code and related agentic software development frameworks
- Provide support, maintenance, and continuous iterative improvement of AI\-generated codebases and deployment pipelines
- Triage/debug application performance, data handling, and security issues, tracing bugs within AI\-generated code to establish corrective prompts and structural code remedies
- Partner with multi\-functional business units and product teams to assess their software needs and translate them into agentic prompt parameters and functional system designs
- Assist leadership in executing "make vs. buy" strategies by leveraging Claude Code to rapidly build and deploy Minimum Viable Products (MVPs) to evaluate internal development velocity against commercial SaaS offerings
- Develop new user interfaces, robust APIs, and web experiences optimized for modern, cloud\-native deployments
- Develop application enhancements and functional modules within new codebases, utilizing advanced context windows and automated validation loops
- Write technical specifications, design system blueprints, and structured engineering documentation tailored for AI ingestion and future code iteration
- Document system architecture changes, code repository structures, and successful agentic prompting patterns to scale institutional knowledge
- Review AI\-generated technical designs and code commits to ensure strict compliance with GE Aerospace engineering, safety, and security guardrails
- Train, mentor, and actively upskill team members on how to effectively utilize Claude Code and agentic workflows
### Education Qualification
- Bachelor’s degree from accredited university or college with minimum of 10 years of professional experience OR Associates degree with minimum of 13 years of professional experience OR High School Diploma with minimum of 15 years of professional experience
- Minimum 7 years of professional experience in IT
- Note: Military experience is equivalent to professional experience
Eligibility Requirement:
- Legal authorization to work in the U.S. is required. We will not sponsor individuals for employment visas, now or in the future, for this job.
### Desired Characteristics
- Demonstrated ability to quickly understand new software architectures and analyze systemic code challenges within a fast\-moving, agentic development loop
- Passionate about application security, secure coding guardrails, prompt defense, and the operational stability of new software
- Organized, thorough, and detail\-oriented, especially when managing automated telemetry and system verification tests
- Collaborates well with others to solve complex software engineering problems and actively incorporates input from both human teammates and AI development agents
- Eager to learn, shares creative ideas, encourages open experimentation, and accepts feedback well in a fast\-paced technology landscape
- Strong analytical skills – strong problem\-solving skills, communicates in a clear and succinct manner, and effectively evaluates technical information/data to make design decisions; anticipates obstacles and develops plans to resolve them
- Deeply interested in current and emerging technologies, keeping a pulse on the state\-of\-the\-art in agentic coding tools, large language models, and multi\-modal application development
- Working knowledge of modern data layers, cloud architectures, and API development paradigms used to sustain rapid software generation
- Demonstrated customer focus – evaluates application decisions through the eyes of the end\-user; builds strong internal relationships and prioritizes clean UI/UX processes
- High level of energy and enthusiasm, with the ability to thrive in a dynamic, fast\-paced setting focused on organizational transformation
- Experience operating within modern developer setups and orchestrating cloud environments
- Experience deploying, scaling, and maintaining net\-new production software applications in an enterprise environment
- Experience with modern git workflows, automated CI/CD deployment pipelines, and version control management
Additional Information:
The base pay range for this position is $174,000 \- $210,000 annually. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary/ commission based on the plan. This posting is expected to close on June 10th, 2026\.
GE Aerospace offers comprehensive benefits and programs to support your health and, along with programs like HealthAhead, your physical, emotional, financial and social wellbeing. Healthcare benefits include medical, dental, vision, and prescription drug coverage; access to a Health Coach from GE Aerospace; and the Employee Assistance Program, which provides 24/7 confidential assessment, counseling and referral services. Retirement benefits include the GE Aerospace Retirement Savings Plan, a 401(k) savings plan with company matching contributions and company retirement contributions, as well as access to Fidelity resources and planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability insurance, life insurance, and paid time\-off for vacation or illness.
GE Aerospace (General Electric Company or the Company) and its affiliates each sponsor certain employee benefit plans or programs (i.e., is a “Sponsor”). Each Sponsor reserves the right to terminate, amend, suspend, replace or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a Sponsor’s welfare benefit plan or program. This document does not create a contract of employment with any individual.
*This role requires access to U.S. export\-controlled information. Therefore, employment will be contingent upon the ability to prove that you meet the status of a U.S. Person as one of the following: U.S. lawful permanent resident, U.S. Citizen, have been granted asylee or refugee status (i.e., a protected individual under the Immigration and Naturalization Act, 8 U.S.C. 1324b(a)(3\)).*
Additional Information
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GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation. 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).
Relocation Assistance Provided: No
\#LI\-Remote \- This is a remote position
Salary Context
This $174K-$210K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At GE Aerospace, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($192K) sits 6% above the category median. Disclosed range: $174K to $210K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
GE Aerospace AI Hiring
GE Aerospace has 3 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Positions span KY, US, Evendale, OH, US, Remote, US. Compensation range: $140K - $210K.
Remote Work Context
Remote AI roles pay a median of $170,000 across 1,926 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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