Software Engineer – AI/ML

🕒 August 6

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GE Aerospace

WebsiteLinkedInAll Job Openings

10,000+ employees

🏭 Manufacturing

🎖️ Defense

💼 Consulting

Manufacturing • Defense • Consulting

GE Aerospace is a world-leading provider of jet and turboprop engines, as well as integrated systems for commercial, military, business, and general aviation aircraft. The company is dedicated to advancing sustainable aviation through the development of efficient aircraft engines compatible with alternative fuels and collaborates across the industry to promote innovation and safety in flight.

📋 Description

• Develop 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 operational datasets into scalable AI capabilities for real-time decision support • Define and evolve AI-powered software products for Commercial Engine Services operations • Create Model Context Protocol 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 applications, including natural language queries, predictive insights, and intelligent recommendations • Provide hands-on AI/ML technical leadership and establish best practices for prompt engineering, model evaluation, experiment tracking, and responsible AI • Partner with executive stakeholders, BI leadership, domain experts, BI developers, platform engineers, and business stakeholders • 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 • Collaborate with data platform teams on data pipelines, data quality, freshness, and feature engineering using Databricks medallion architecture • Establish MLOps practices including experiment tracking, model versioning, automated evaluation pipelines, and A/B testing • Implement monitoring, observability, and automated alerting for model performance, data drift, latency, and error rates • Design vector database architectures and semantic search capabilities 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 compliance with AI governance policies • Drive the AI/ML roadmap by identifying use cases, evaluating technologies, and building proof-of-concepts • Establish reusable AI/ML components, templates, and reference architectures • Communicate AI/ML concepts, tradeoffs, and results through documentation, executive presentations, and demonstrations • Mentor the team on AI integration, prompt engineering, and model usage • Drive products through deployment, monitoring, iteration, and continuous accuracy improvement

🎯 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 using appropriate 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 • 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 MLOps, CI/CD, automated testing, secure coding, scalability, documentation-as-code, refactoring, and performance engineering • Experience with monitoring and observability for AI/ML systems • Experience designing vector database architectures and semantic search for RAG applications • Experience building LLM evaluation frameworks and automated prompt/model-output testing • Knowledge of bias detection, explainability using SHAP or LIME, privacy-preserving techniques, and enterprise AI governance • Ability to translate AI/ML capabilities into measurable business outcomes • Ability to break down ambiguous AI problems, write clear problem statements, and estimate model development effort • Strong written and verbal communication skills • Legally authorized to work in the United States • Successful completion of a drug screen, as applicable

🏖️ Benefits

• Annual discretionary bonus based on a percentage of base salary • 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 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 • Professional development • Relocation assistance not provided