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Software Engineer Ai Model Training Jobs in Ohio

GE Aerospace

Software Engineer AI/ML

Evendale, OH · On-site

$109K - $132K/yr

You'll spend most of your time developing AI/ML products by training models, developing ... scientists, software engineers, and business stakeholders * Effective collaborator who works ...

ERP Suites

AI Software Engineer

Loveland, OH · On-site +1

ERP Suites is seeking AI Software Engineers to join our growing team and contribute to the ... Prepare, manage, and validate data for AI models and inference workflows . * Optimize prompt ...

ERP Suites

AI Software Engineer

Cincinnati, OH · On-site

ERP Suites is seeking AI Software Engineers to join our growing team and contribute to the ... Prepare, manage, and validate data for AI models and inference workflows . * Optimize prompt ...

John Deere

Software Engineer - AI Solutions Poznań, Poland Your responsibilities: * Works closely and ... Prompt engineering, API-based model usage, Retrieval-augmented generation (RAG) basics.

DataAnnotation

Software Engineer - AI Trainer

Toledo, OH · On-site +1

$50 - $100/hr

Our platform offers an engaging blend of flexibility and challenge: you'll work closely with state-of-the-art AI models to take on programming tasks that include creating and solving challenging ...

DataAnnotation

Software Engineer - AI Trainer

Dayton, OH · On-site +1

$50 - $100/hr

Our platform offers an engaging blend of flexibility and challenge: you'll work closely with state-of-the-art AI models to take on programming tasks that include creating and solving challenging ...

John Deere

Staff Software Engineer - AI Solutions Poznań, Poland Your responsibilities:​ * Participate and ... model at Business Garden in Poznań. * Opportunities for professional development within the ...

Aegis Ventures

Senior Software Engineer

Cleveland, OH · On-site +1

$118K - $156K/yr

... device innovation, AI model training, and improved patient care. Leveraging its strategic ... About the Job As a Senior Software Engineer , help build and scale a category-defining healthcare ...

Vurvey Labs

AI Software/ Data Engineer

Cincinnati, OH · On-site

$111K - $134K/yr

Vurvey Labs is an applied AI company developing models and platforms that enhance human collaboration. They are seeking a versatile AI Software Engineer to bridge AI initiatives with production ...

Aegis Ventures

Principal Software Engineer

Cleveland, OH · On-site +1

$130K - $175K/yr

... device innovation, AI model training, and improved patient care. Leveraging its strategic ... About the Job As a Principal Software Engineer at Avandra Imaging, you'll serve as a hands-on ...

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Software Engineer Ai Model Training information

What does a software engineer AI model training do?

A Software Engineer specializing in AI Model Training is responsible for designing, developing, and optimizing machine learning models. Their work involves preparing and processing large datasets, selecting appropriate algorithms, implementing training pipelines, and evaluating model performance. They collaborate closely with data scientists and other engineers to ensure that AI models are accurate, efficient, and suitable for deployment in real-world applications. Additionally, they may help maintain infrastructure for model training and contribute to research and development of new AI techniques.

What are the key skills and qualifications needed to thrive as a software engineer AI model training?

To excel as a Software Engineer in AI Model Training, you need strong programming skills (especially in Python), a solid grasp of machine learning fundamentals, and typically a degree in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, familiarity with data processing tools, and sometimes certifications in AI or ML are highly valuable. Analytical thinking, problem-solving, and effective collaboration enhance your ability to develop and refine complex AI models. These skills ensure that AI solutions are robust, scalable, and aligned with organizational goals in a rapidly evolving technological landscape.

What are some common challenges faced by software engineers AI model training, and how can they be addressed?

Software Engineers focusing on AI model training often encounter challenges such as managing large datasets, ensuring data quality, and optimizing model performance. Addressing these issues typically involves close collaboration with data scientists, domain experts, and DevOps engineers to streamline the data pipeline and refine training processes. Staying up to date with the latest advancements in machine learning frameworks and tools can also help overcome technical hurdles. Regular code reviews and cross-functional meetings further support problem-solving and foster a productive work environment.

What is the difference between Software Engineer Ai Model Training vs Data Scientist?

AspectSoftware Engineer Ai Model TrainingData Scientist
Required CredentialsBachelor's in CS, related field; experience with ML frameworksBachelor's or higher in CS, statistics, or related field; strong analytical skills
Work EnvironmentDevelopment teams, AI labs, cloud platformsData analysis, research environments, business units
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, consulting

While both roles involve working with data and machine learning, Software Engineer Ai Model Training focuses on developing and optimizing AI models through coding and engineering practices. Data Scientists analyze data, build models, and generate insights. The roles often collaborate but differ in their core responsibilities and skill sets.

Can I get paid to train AI models?

Yes, software engineers and AI specialists can be paid to train AI models, especially in roles that involve developing, fine-tuning, and optimizing machine learning algorithms. These positions often require knowledge of programming languages like Python, experience with machine learning frameworks, and access to computational resources. Compensation varies based on experience, location, and the complexity of the models being trained.

How to become a software engineer AI model trainer?

To become a software engineer AI model trainer, you should have a strong background in computer science, programming skills in languages like Python, and experience with machine learning frameworks such as TensorFlow or PyTorch. Gaining knowledge in data preprocessing, model evaluation, and working with large datasets is essential, along with relevant certifications or advanced degrees in AI or related fields.

What are popular job titles related to Software Engineer Ai Model Training jobs in Ohio?

For Software Engineer Ai Model Training jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Software Engineer Ai Model Training jobs in Ohio look for?

The top searched job categories for Software Engineer Ai Model Training jobs in Ohio are:

What cities in Ohio are hiring for Software Engineer Ai Model Training jobs?

Cities in Ohio with the most Software Engineer Ai Model Training job openings:

Software Engineer Ai Model Training jobs near you
Infographic showing various Software Engineer Ai Model Training job openings in Ohio as of July 2026, with employment types broken down into 75% Full Time, 23% Part Time, and 2% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution.

Software Engineer AI/ML

Evendale, OH • On-site

GE Aerospace
Aerospace Product and Parts Manufacturing • 10K+ employees
Learn more about GE Aerospaceexternal

$109K - $132K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago

Key responsibilities

  • 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.

  • Collaborate with BI and data platform teams to develop AI capabilities, integrate AI features into applications, and ensure data quality for AI/ML models.

GE Aerospace rating

8.8

Company rating: 8.8 out of 10

Based on 186 frontline employees who took The Breakroom Quiz

13th of 72 rated aerospace companies

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, and evolve AI-powered software products that accelerate Commercial Engine Services operations-including LLM applications, machine learning models, and intelligent automation for supply chain optimization
  • Create Model Context Protocol (MCP) servers that package domain-specific AI capabilities for reuse across the enterprise.
  • Package AI/ML models as robust, well-documented APIs that enable seamless integration into dashboards, applications, and operational workflows.
  • Collaborate with BI team to embed AI features into existing applications that enable natural language queries, predictive insights, and intelligent recommendations directly within user-facing applications

Technical Leadership & Collaboration
  • Provide hands-on AI/ML technical leadership for our modernization initiative, setting best practices for prompt engineering, model evaluation, experiment tracking, and responsible AI development
  • Partner with executive stakeholders and BI leadership to understand business challenges and translate 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, and A/B testing frameworks for continuous model improvement
  • Drive world-class quality through rigorous SDLC practices: Lean/Agile/XP, CI/CD, automated testing, secure coding, scalability patterns, documentation-as-code, refactoring, and performance engineering
  • Implement monitoring and observability for AI/ML systems to track model performance, data drift, prediction latency, and error rates; build automated alerting for model degradation
  • Design vector database architectures and semantic search capabilities to power RAG applications; optimize retrieval strategies for accuracy and latency
  • Build evaluation frameworks for LLM applications-measuring response quality, accuracy, relevance, and hallucination rates; establish automated testing for prompt templates and model outputs
  • Ensure responsible AI practices including bias detection, explainability (SHAP, LIME), privacy-preserving techniques, and compliance with enterprise AI governance policies

Innovation & Strategy
  • Drive the AI/ML roadmap for Commercial Engine Services BI team by identifying high-impact use cases, evaluating emerging AI technologies, and building proof-of-concepts that demonstrate business value
  • Stay current on LLM advancements, ML frameworks, vector databases, and AI application patterns; bring practical innovations that improve decision speed and operational outcomes
  • Engage domain experts to ensure successful transfer of complex operational knowledge into AI models and intelligent systems
  • Establish reusable AI/ML components, templates, and reference architectures that accelerate future development and enable the BI team to leverage AI capabilities independently
  • 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, C#, TypeScript-based on system needs)
  • Proven experience building data platforms and production LLM-powered applications; strong understanding of prompt engineering, retrieval-augmented generation, and vector databases
  • Strong foundation in supervised/unsupervised learning, time-series forecasting, classification, and optimization
  • Experience with MLflow, model registries, automated training pipelines, A/B testing frameworks, and model monitoring; strong DevOps collaboration skills
  • Expertise in development platforms and services: AWS, Visual Studio, Databricks, GitHub, etc.
  • Experience building REST APIs (FastAPI, Flask) for model serving; understanding of authentication, rate limiting, versioning, and API documentation

Domain & Business Acumen
  • Experience building AI/ML solutions for supply chain, manufacturing, maintenance, or operations analytics is a strong plus
  • Understands business metrics and can translate AI/ML capabilities into quantifiable business outcomes (cost savings, time reduction, forecast accuracy improvement)
  • Skilled in breaking down ambiguous AI problems, writing clear problem statements, and estimating model development effort accurately
  • Stays current on AI/ML industry trends (LLM advancements, new frameworks, emerging techniques); brings practical innovations backed by proof-of-concepts

Leadership & Collaboration
  • Leads by example through delivering AI/ML products while mentoring team on AI integration, prompt engineering, and model usage
  • Able to work through ambiguity and drive alignment between AI capabilities and business needs; communicates model limitations, confidence intervals, and uncertainty clearly to non-technical stakeholders
  • Continuously measures solutions against user expectations while balancing competing priorities and maintaining build quality.

Personal Attributes
  • Strong written and verbal communication skills with the ability to explain complex AI/ML concepts simply and translate effectively between data scientists, software engineers, and business stakeholders
  • Effective collaborator who works seamlessly with BI developers, platform engineers, and business stakeholders
  • Business-minded approach that focuses on operational metrics, user needs, and business impact while designing AI solutions that solve real problems rather than technical exercises
  • Persists to completion by driving AI/ML products through deployment, monitoring, and iteration while taking ownership of model performance and continuously improving accuracy

The base pay range for this position is $112,000-150,000. The specific pay offered may be influenced by a variety of factors, including the candidate's experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary/ commission based on the plan. This posting is expected to close on August 14th, 2026.
GE Aerospace offers comprehensive benefits and programs to support your health and, along with programs like HealthAhead, your physical, emotional, financial and social wellbeing. Healthcare benefits include medical, dental, vision, and prescription drug coverage; access to a Health Coach from GE Aerospace; and the Employee Assistance Program, which provides 24/7 confidential assessment, counseling and referral services. Retirement benefits include the GE Aerospace Retirement Savings Plan, a 401(k) savings plan with company matching contributions and company retirement contributions, as well as access to Fidelity resources and planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability insurance, life insurance, and paid time-off for vacation or illness.
GE Aerospace (General Electric Company or the Company) and its affiliates each sponsor certain employee benefit plans or programs (i.e., is a "Sponsor"). Each Sponsor reserves the right to terminate, amend, suspend, replace or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a Sponsor's welfare benefit plan or program. This document does not create a contract of employment with any individual.
This role will require in-person attendance for New Hire Orientation on Day 1.
#LI-JR1
Additional Information
GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation. GE Aerospace is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE Aerospace will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable). Employees may also be subject to random and reasonable-suspicion drug and alcohol testing.
Relocation Assistance Provided: No
#LI-Remote - This is a remote position

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