Software Engineer – AI/ML

This is a fully remote position, open to applicants in Ohio.

📋 Description

• Design, develop, deliver, and maintain AI/ML products, including applications powered by LLMs, forecasting models, anomaly detection systems, and intelligent agents.

• Oversee the entire AI/ML lifecycle, from requirements gathering and model design to training, assessment, API development, deployment, and operational support.

• Transform complex operational datasets into scalable AI capabilities for real-time decision-making.

• Define and enhance AI-driven software products that support Commercial Engine Services operations, supply chain optimization, and intelligent automation.

• Create Model Context Protocol (MCP) servers to provide reusable domain-specific AI capabilities.

• Package AI/ML models as well-documented APIs for dashboards, applications, and operational workflows.

• Integrate AI features into existing BI applications, including natural language queries, predictive insights, and intelligent recommendations.

• Provide hands-on technical leadership in areas such as prompt engineering, model assessment, experiment tracking, and responsible AI development.

• Collaborate with executive stakeholders, BI leadership, analytics teams, data platform teams, and domain experts to translate business requirements into AI/ML capabilities.

• Deploy AI/ML models reliably to AWS, implementing monitoring, logging, and performance optimization.

• Convert requirements into a prioritized AI/ML product backlog, ensuring delivery aligns with timelines, quality standards, and business objectives.

• Design data pipelines using the Databricks medallion architecture, ensuring data quality, freshness, and feature engineering.

• Establish MLOps practices, including model versioning, automated evaluation pipelines, and A/B testing frameworks.

• Implement monitoring and observability solutions for model performance, data drift, latency, and error rates, complete with automated alerting.

• Design vector database architectures and semantic search components for RAG applications.

• Develop LLM evaluation frameworks and automated testing for prompts and model outputs.

• Ensure adherence to responsible AI practices, encompassing bias detection, explainability, privacy-preserving techniques, and compliance with AI governance.

• Lead the AI/ML roadmap, identify high-impact use cases, assess emerging technologies, and create proof-of-concepts.

• Develop reusable AI/ML components, templates, and reference architectures.

• Communicate AI/ML concepts, trade-offs, and outcomes through documentation, executive presentations, and live demonstrations.

⛳️ Requirements

• Bachelor's Degree in Computer Science, Data Science, Statistics, Engineering, or a related field from an accredited institution.

• At least 3 years of practical AI/ML engineering experience in building and deploying machine learning models and/or AI-powered applications in production.

• Proficiency in production-quality coding with technologies such as Python, Java, C#, or TypeScript.

• Experience in building data platforms and production-level LLM-powered applications.

• Strong knowledge of prompt engineering, retrieval-augmented generation, and vector databases.

• Solid foundation in supervised and unsupervised learning, time-series forecasting, classification, and optimization.

• Familiarity with MLflow, model registries, automated training pipelines, A/B testing frameworks, and model monitoring.

• Expertise in AWS, Visual Studio, Databricks, GitHub, or similar development platforms and services.

• Experience in building REST APIs using FastAPI or Flask.

• Understanding of authentication, rate limiting, API versioning, and API documentation.

• Experience in supply chain, manufacturing, maintenance, or operations analytics is highly desirable.

• Ability to convert AI/ML capabilities into measurable business outcomes.

• Capability to deconstruct ambiguous AI challenges, draft clear problem statements, and estimate model development efforts.

• Awareness of current AI/ML industry trends and the ability to develop proof-of-concepts.

• Ability to mentor team members in AI integration, prompt engineering, and model usage.

• Skill in clearly communicating model limitations, confidence intervals, and uncertainties to non-technical stakeholders.

• Strong written and verbal communication abilities.

• Effective collaboration with BI developers, platform engineers, and business stakeholders.

• Capacity to drive AI/ML products through deployment, monitoring, and iterative improvement.

• Legally authorized to work in the United States.

• Successful completion of a drug screening, if 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 according to the plan.

• Medical, dental, vision, and prescription drug coverage.

• Access to a Health Coach from GE Aerospace.

• Employee Assistance Program offering 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.

• Opportunities for professional development.

• Engaging and challenging careers.

• Competitive compensation.