Software Engineer AI/ML
AI summary of the role
Build and deploy production-grade AI/ML products—LLM applications, forecasting models, anomaly detection, and intelligent agents—for GE Aerospace's Commercial Engine Services operations.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Design, build, deliver, and maintain AI/ML products including LLM-powered applications, forecasting models, anomaly detection systems, and intelligent agents
- Create Model Context Protocol (MCP) servers and package AI/ML models as well-documented APIs for enterprise reuse
- Establish MLOps practices: experiment tracking (MLflow, Weights & Biases), model versioning, automated evaluation, and A/B testing
- Design vector database architectures and semantic search for RAG applications; build evaluation frameworks for LLM response quality and hallucination rates
What you’ll bring
- Bachelor's Degree in Computer Science, Data Science, Statistics, Engineering, or related field
- Minimum 3 years of hands-on AI/ML engineering experience building and deploying models or AI-powered applications to production
- Proven experience building production LLM-powered applications with prompt engineering, RAG, and vector databases
- Strong foundation in supervised/unsupervised learning, time-series forecasting, classification, and optimization
Technologies
Python · Java · C# · TypeScript · AWS · Databricks · MLflow · Weights & Biases · FastAPI · Flask · GitHub · RAG
About GE Aerospace
Designs and manufactures jet engines, components, and integrated avionics/mission systems for commercial and military aircraft, plus aftermarket MRO services worldwide.
Public · 5000+ people
Source and classification
Internal deployment & tooling · Evidence for this classification:
Job Description Summary The CES Business Intelligence team is building the next generation of AI-powered solutions for commercial, contracts, and operations. We're looking for an AI Engineer to help transform GE Aerospace operational data into production-grade machine learning pipelines, models, and LLM-powered applications. This is a multi-faceted engineering role. You'll spend most of your time developing AI/ML products by training models, developing applications, and creating APIs. You will partner closely with analytics teams to enable AI within our existing operational tools. You'll also contribute to AI strategy and partner with executive stakeholders to align on requirements, success metrics, and business impact. We're looking for someone who's excited to expand their technical skillset in AI/ML and deliver advanced solutions that directly impact daily operations. What you'll
More from the job description
Job Description Summary The CES Business Intelligence team is building the next generation of AI-powered solutions for commercial, contracts, and operations. We're looking for an AI Engineer to help transform GE Aerospace operational data into production-grade machine learning pipelines, models, and LLM-powered applications. This is a multi-faceted engineering role. You'll spend most of your time developing AI/ML products by training models, developing applications, and creating APIs. You will partner closely with analytics teams to enable AI within our existing operational tools. You'll also contribute to AI strategy and partner with executive stakeholders to align on requirements, success metrics, and business impact. We're looking for someone who's excited to expand their technical skillset in AI/ML and deliver advanced solutions that directly impact daily operations. What you'll do: 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: requirements analysis, model design, training, evaluation, API development, deployment, and operational support. Convert complex operational datasets into scalable AI capabilities that enable real-time decision support. Job Description Roles and Responsibilities: AI/ML Product Development Define, build, [... source excerpt omitted ...] slate operational needs into AI/ML capabilities Ensure AI/ML models deploy reliably to AWS infrastructure with proper monitoring, logging, and performance optimization Translate requirements into a prioritized backlog of AI/ML products, driving delivery to required timelines, quality standards, and measurable business outcomes Collaborate with data platform teams to design data pipelines that feed AI/ML models to ensure data quality, freshness, and proper feature engineering from the Databricks medallion architecture AI/ML Infrastructure & MLOps Establish MLOps practices including experiment tracking (MLflow, Weights & Biases), model versioning, automated evaluation pipelines, a [... source excerpt omitted ...] pendently Communicate AI/ML concepts, tradeoffs, and results to non-technical stakeholders through clear documentation, executive presentations, and live demonstrations Required Qualifications 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 Desired Characteristics Technical Expertise Write production-quality code that meets standards and delivers intended functionality using the most appropriate technologies for the project (e.g., Python, Java
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