Software Engineer - AI/ML

About The Company

GE Aerospace, a leading division of General Electric, is renowned for its innovation and excellence in the aerospace industry. Committed to shaping the future of flight, GE Aerospace leverages cutting-edge technology and a global footprint to deliver advanced aircraft engines, systems, and solutions that enhance safety, efficiency, and sustainability. The company fosters a dynamic work environment that encourages continuous learning, collaboration, and technological advancement. With a focus on operational excellence and customer satisfaction, GE Aerospace remains at the forefront of aerospace innovation, supporting commercial, military, and business aviation sectors worldwide.

About The Role

We are seeking a highly skilled AI Engineer to join the CES Business Intelligence team at GE Aerospace. This pivotal role involves developing next-generation AI-powered solutions tailored for commercial, contracts, and operations domains. The AI Engineer will be instrumental in transforming complex operational data into scalable, production-grade machine learning pipelines, models, and large language model (LLM)-powered applications. The ideal candidate will collaborate closely with analytics teams and executive stakeholders to define requirements, design innovative AI solutions, and drive strategic initiatives that enhance operational efficiency and decision-making. This role offers an exciting opportunity to work on diverse facets of AI/ML development, including model training, application development, API creation, and deployment, all aimed at delivering measurable business impact.

Qualifications

• Bachelor's Degree in Computer Science, Data Science, Statistics, Engineering, or related field from an accredited institution
• Minimum of 3 years of hands-on experience in AI/ML engineering, including building and deploying machine learning models and AI-powered applications
• Proficiency in programming languages such as Python, Java, C#, or TypeScript
• Experience with MLflow, model registries, automated training pipelines, and model monitoring tools
• Strong understanding of supervised and unsupervised learning, time-series forecasting, classification, and optimization techniques
• Experience with cloud platforms such as AWS, Databricks, and related DevOps tools like GitHub
• Ability to develop REST APIs using frameworks like FastAPI or Flask, with knowledge of authentication and versioning
• Experience in building data pipelines, feature engineering, and working within data architectures such as Databricks medallion architecture
• Knowledge of vector databases, semantic search, and retrieval-augmented generation (RAG) applications
• Understanding of responsible AI practices, including bias detection, explainability, privacy, and compliance standards
• Strong communication skills, with the ability to translate complex technical concepts to non-technical stakeholders
• Demonstrated leadership capabilities and a collaborative mindset

Responsibilities

• Design, develop, and deploy AI/ML products including LLM applications, forecasting models, anomaly detection systems, and intelligent agents
• Lead the full AI/ML lifecycle from requirements gathering, model design, training, evaluation, to deployment and operational support
• Build reusable AI capabilities through Model Context Protocol (MCP) servers and package models as APIs for seamless integration
• Embed AI features into existing operational tools to enable natural language queries, predictive insights, and automated recommendations
• Provide technical leadership on AI/ML best practices, prompt engineering, and responsible AI development
• Collaborate with data platform teams to design and optimize data pipelines, ensuring data quality and proper feature engineering
• Implement MLOps practices including experiment tracking, model versioning, automated testing, and continuous integration/continuous deployment (CI/CD)
• Establish monitoring, logging, and alerting systems to track model performance, data drift, and system health
• Design vector database architectures and optimize retrieval strategies for RAG applications
• Develop evaluation frameworks for LLM response quality, relevance, and hallucination mitigation
• Ensure AI solutions adhere to ethical standards, bias mitigation, explainability, and privacy regulations
• Drive innovation by exploring emerging AI technologies, building proof-of-concept projects, and establishing reusable components
• Communicate technical findings, project status, and strategic insights to diverse stakeholders, including executives

Benefits

• Competitive base salary within the range of $112,000 to $150,000, commensurate with experience and skills
• Annual discretionary bonus and performance-based incentives
• Comprehensive health benefits including medical, dental, vision, and prescription coverage
• Access to wellness programs such as HealthAhead and support from health coaches
• Retirement savings plan with company matching contributions and financial planning resources
• Tuition assistance, adoption support, and paid parental leave
• Disability and life insurance coverage
• Paid time off for vacation, personal leave, and illness
• Opportunities for professional development, training, and career advancement