Software Engineer – AI/ML

🕒 August 6

🏈 Ohio – Remote

🏈 Ohio – Remote

💵 $112k - $150k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

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GE Aerospace

WebsiteLinkedInAll Job Openings

10,000+ employees

🚀 Aerospace

🏭 Manufacturing

🎖️ Defense

💰 $2G Post-IPO Debt - GE Aerospace on 2025-07

Aerospace • Manufacturing • Defense

GE Aerospace is a global aerospace company that designs, manufactures, and services jet engines, components, and integrated systems for commercial and military aircraft. Headquartered in Cincinnati, Ohio, the company operates 60+ manufacturing locations, 15+ overhaul and component repair sites, and multiple engineering centers across 24 countries, employing roughly 53,000 people. GE Aerospace invests heavily in R&D (reported $2. 75B including customer/partner funding), supports large-scale commercial aviation (3. 4 billion passengers flew with GE technology in 2024) and maintains a fleet of about 45,000 engines in service. The company emphasizes U. S. manufacturing, workforce development, and a lean operating model called FLIGHT DECK, and is a major defense supplier supporting military aviation.

📋 Description

• Design, build, deliver, and maintain AI/ML products, including LLM-powered applications, forecasting models, anomaly detection systems, and intelligent agents • Own the full AI/ML lifecycle from requirements analysis and model design through training, evaluation, API development, deployment, and operational support • Convert complex operational datasets into scalable AI capabilities for real-time decision support • Define and evolve AI-powered software products supporting Commercial Engine Services operations, supply chain optimization, and intelligent automation • Create Model Context Protocol (MCP) servers for reusable domain-specific AI capabilities • Package AI/ML models as documented APIs for dashboards, applications, and operational workflows • Embed AI features into existing BI applications, including natural-language queries, predictive insights, and intelligent recommendations • Provide hands-on technical leadership for prompt engineering, model evaluation, experiment tracking, and responsible AI development • Partner with executive stakeholders, BI leadership, analytics teams, data platform teams, and domain experts to translate business needs into AI/ML capabilities • Deploy AI/ML models reliably to AWS with monitoring, logging, and performance optimization • Translate requirements into a prioritized AI/ML product backlog and drive delivery against timelines, quality standards, and business outcomes • Design data pipelines using the Databricks medallion architecture, ensuring data quality, freshness, and feature engineering • Establish MLOps practices, model versioning, automated evaluation pipelines, and A/B testing frameworks • Implement monitoring and observability for model performance, data drift, latency, and error rates, with automated alerting • Design vector database architectures and semantic search for RAG applications • Build LLM evaluation frameworks and automated testing for prompts and model outputs • Ensure responsible AI practices, including bias detection, explainability, privacy-preserving techniques, and AI governance compliance • Drive the AI/ML roadmap, identify high-impact use cases, evaluate emerging technologies, and build proof-of-concepts • Establish reusable AI/ML components, templates, and reference architectures • Communicate AI/ML concepts, tradeoffs, and results through documentation, executive presentations, and live demonstrations

🎯 Requirements

• Bachelor's Degree in Computer Science, Data Science, Statistics, Engineering, or related field from an accredited college or university • Minimum of 3 years of hands-on AI/ML engineering experience building and deploying machine learning models and/or AI-powered applications to production • Production-quality coding skills in technologies such as Python, Java, C#, or TypeScript • Experience building data platforms and production LLM-powered applications • Strong understanding of prompt engineering, retrieval-augmented generation, and vector databases • Strong foundation in supervised and unsupervised learning, time-series forecasting, classification, and optimization • Experience with MLflow, model registries, automated training pipelines, A/B testing frameworks, and model monitoring • Expertise with AWS, Visual Studio, Databricks, GitHub, or similar development platforms and services • Experience building REST APIs using FastAPI or Flask • Understanding of authentication, rate limiting, API versioning, and API documentation • Experience with supply chain, manufacturing, maintenance, or operations analytics is a strong plus • Ability to translate AI/ML capabilities into quantifiable business outcomes • Ability to break down ambiguous AI problems, write clear problem statements, and estimate model development effort • Knowledge of current AI/ML industry trends and ability to develop proof-of-concepts • Ability to mentor team members on AI integration, prompt engineering, and model usage • Ability to communicate model limitations, confidence intervals, and uncertainty clearly to non-technical stakeholders • Strong written and verbal communication skills • Effective collaboration with BI developers, platform engineers, and business stakeholders • Ability to drive AI/ML products through deployment, monitoring, and iteration • Legally authorized to work in the United States • Successful completion of a drug screen, as applicable; employees may be subject to random and reasonable-suspicion drug and alcohol testing

🏖️ Benefits

• Annual discretionary bonus based on a percentage of base salary/commission based on the plan • Medical, dental, vision, and prescription drug coverage • Access to a Health Coach from GE Aerospace • Employee Assistance Program with 24/7 confidential assessment, counseling, and referral services • GE Aerospace Retirement Savings Plan • 401(k) savings plan with company matching contributions • 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 • Professional development • Challenging careers • Competitive compensation