ZipRecruiter

Log In

1

Privacy Preserving Machine Learning Jobs in Ohio

GE Aerospace

Software Engineer AI/ML

Evendale, OH · On-site

$109K - $132K/yr

... machine learning pipelines, models, and LLM-powered applications. This is a multi-faceted ... LIME), privacy-preserving techniques, and compliance with enterprise AI governance policies ...

Orion

Senior Privacy & AI Risk Analyst

Cincinnati, OH · Hybrid

Perform privacy reviews and impact assessments for AI and machine-learning use cases that involve personal information, evaluating data minimization, purpose limitation, transparency, and automated ...

Flexjet

AI Data Engineer

Cleveland, OH · On-site

$111K - $133K/yr

DUTIES & RESPONSIBILITIES Design, build, and maintain data pipelines for AI and machine learning ... and privacy standards Strong analytical and problem-solving skills Attention to detail and data ...

Flexjet

AI Data Engineer

Cleveland, OH · On-site

$111K - $133K/yr

DUTIES & RESPONSIBILITIES Design, build, and maintain data pipelines for AI and machine learning ... and privacy standards Strong analytical and problem-solving skills Attention to detail and data ...

Flexjet

AI Data Engineer

Cleveland, OH · On-site

$111K - $133K/yr

DUTIES & RESPONSIBILITIES · Design, build, and maintain data pipelines for AI and machine learning ... privacy standards · Strong analytical and problem-solving skills · Attention to detail and data ...

Blacklight Network

Identity Engineer

Columbus, OH · On-site

$130K - $170K/yr

Every machine, AI agent, and person gets a built-in, unforgeable identity, with security baked into ... privacy-preserving telemetry. How We Work We use AI agents heavily in our own engineering. We ...

New

Flexjet

Senior Data Scientist

Cleveland, OH · On-site

The ideal candidate has hands-on experience with machine learning, large language models (LLMs ... privacy, and security standards Support model explainability and documentation requirements ...

Flexjet

Senior Data Scientist

Cleveland, OH · On-site

The ideal candidate has hands-on experience with machine learning, large language models (LLMs ... privacy, and security standards Support model explainability and documentation requirements ...

Flexjet

Senior Data Scientist

Cleveland, OH · On-site

The ideal candidate has hands-on experience with machine learning, large language models (LLMs ... governance, privacy, and security standards · Support model explainability and documentation ...

Flexjet

Director of AI Engineering

Cleveland, OH · On-site

Oversee the production deployment of machine learning and LLM-powered applications, including RAG ... Ensure compliance with responsible AI, security, risk management, data privacy, auditability ...

previous pagenext page

Showing results 21-40

All JobsPrivacy Preserving Machine Learning JobsPrivacy Preserving Machine Learning Jobs in Ohio

Privacy Preserving Machine Learning information

What is privacy preserving machine learning?

Privacy preserving machine learning refers to techniques and methods that allow data analysis and model training while protecting sensitive information. This field focuses on ensuring that personal or confidential data is not exposed or compromised during the development and deployment of machine learning models. Approaches such as federated learning, differential privacy, and homomorphic encryption are commonly used. These methods enable organizations to leverage data for insights and predictions without violating privacy regulations or risking data breaches. Privacy preserving machine learning is especially important in industries like healthcare, finance, and any sector handling personal data.

What are the key skills and qualifications needed to thrive as a privacy preserving machine learning engineer?

To thrive as a Privacy Preserving Machine Learning Engineer, you need a strong background in machine learning, data privacy techniques (such as differential privacy or federated learning), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow Privacy, PySyft, and privacy-enhancing technologies, along with certifications in data security or privacy, are often required. Strong problem-solving abilities, meticulous attention to detail, and the ability to communicate complex technical concepts clearly set top professionals apart. These skills ensure the development of robust machine learning models that protect sensitive data while delivering valuable insights, maintaining compliance and trust.

What are some common challenges faced by professionals working in privacy preserving machine learning roles?

Professionals in Privacy Preserving Machine Learning often encounter challenges such as balancing model accuracy with strict privacy requirements, selecting appropriate privacy-preserving techniques (like differential privacy or federated learning), and ensuring compliance with evolving data protection regulations. Collaborative projects may also involve coordinating with legal, data security, and software engineering teams to implement robust solutions. Additionally, staying updated with the latest research and adapting to new threats or vulnerabilities is a continuous part of the role.

What is the difference between Privacy Preserving Machine Learning vs Data Scientist?

AspectPrivacy Preserving Machine LearningData Scientist
Required CredentialsTypically requires knowledge of machine learning, data privacy, and security certificationsRequires degrees in data science, statistics, or related fields; certifications like Certified Data Scientist are common
Work EnvironmentWorks in research, development, and implementation of privacy-focused ML models, often in tech or finance sectorsAnalyzes data, builds models, and provides insights across various industries including marketing, finance, and healthcare
Employer & Industry UsageUsed by organizations prioritizing data privacy, such as healthcare, finance, and tech companiesEmployed across diverse sectors for data analysis, predictive modeling, and decision support

Privacy Preserving Machine Learning focuses on developing models that protect data privacy during training and inference, while Data Scientists analyze and interpret data to generate insights. Both roles require strong analytical skills, but Privacy Preserving Machine Learning emphasizes security and privacy techniques, whereas Data Scientists focus on data analysis and modeling.

What are popular job titles related to Privacy Preserving Machine Learning jobs in Ohio?

For Privacy Preserving Machine Learning jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Privacy Preserving Machine Learning jobs in Ohio look for?

The top searched job categories for Privacy Preserving Machine Learning jobs in Ohio are:

What cities in Ohio are hiring for Privacy Preserving Machine Learning jobs?

Cities in Ohio with the most Privacy Preserving Machine Learning job openings:

Privacy Preserving Machine Learning jobs near you

Software Engineer AI/ML

GE Aerospace

Evendale, OH • On-site

$109K - $132K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 29 days ago

GE Aerospace rating

8.8

Company rating: 8.8 out of 10

Based on 185 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

What GE Aerospace employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply