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Privacy Preserving Machine Learning Jobs in Cleveland, OH

Accenture

Lead AI / ML Engineer

Cleveland, OH · On-site

$99K - $130K/yr

Certifications in AI, machine learning, or data science. * + 6 years of experience in projects focused on ethical AI or AI for social good. * Knowledge of AI ethics, data privacy, and regulatory ...

Further

Senior Data Engineer

Cleveland, OH · Hybrid

$102K - $139K/yr

... Machine Learning applications. This is a high-impact role where you will set the standards for data ... privacy rights here.

Further

Senior Data Engineer

Cleveland, OH · On-site

$102K - $139K/yr

... Machine Learning applications. This is a high-impact role where you will set the standards for data ... privacy rights here.

Dealer Tire

Information Security Engineer

Cleveland, OH

$95K - $115K/yr

... and machine learning, intrusion detection and prevention, and various anti-malware solutions to ... privacy protection, network security practices, and security framework compliance to projects and ...

Further

AI Strategist (CLE)

Cleveland, OH · On-site

$117K - $152K/yr

AI / Machine Learning / advanced analytics experience in a highly-regulated industry (healthcare, ... privacy rights here.

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Showing results 21-40

All JobsPrivacy Preserving Machine Learning JobsPrivacy Preserving Machine Learning Jobs in Cleveland, OH

Privacy Preserving Machine Learning information

See Cleveland, OH salary details

$96.5K

$112K

$125.6K

How much do privacy preserving machine learning jobs pay per year?

As of Aug 12, 2026, the average yearly pay for privacy preserving machine learning in Cleveland, OH is $112,020.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $125,100.00 per year, depending on experience, location, and employer.

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 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 job categories do people searching Privacy Preserving Machine Learning jobs in Cleveland, OH look for? The top searched job categories for Privacy Preserving Machine Learning jobs in Cleveland, OH are:
What cities near Cleveland, OH are hiring for Privacy Preserving Machine Learning jobs? Cities near Cleveland, OH with the most Privacy Preserving Machine Learning job openings:
Privacy Preserving Machine Learning jobs near you

Program Manager AI and Data

Supply Technologies LLC

Cleveland, OH • On-site

$50.25 - $68/hr

Full-time

Posted 9 days ago

Supply Technologies rating

4.7

Company rating: 4.7 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

Job description

Position Overview
We are seeking an execution-focused Program Manager for Data and AI to lead the digital transformation of our hybrid global supply chain network. In this role, you will bridge the gap between legacy operations, our modern SAP S/4HANA digital core, and advanced data science. You will orchestrate cross-functional teams to build scalable machine learning models and intelligent automation that consume and harmonize data across a fragmented ERP landscape. Your work will directly unlock the power of multi-system data to optimize inventory, embed predictive forecasting, and drive autonomous decision-making across our end-to-end supply chain.
Department: Information Technology / Data Science / Innovation
  • Reports To: Director of Data, Analytics and Development
  • Employment Type: Full-time or Contract to Hire
  • Location: On-Site
Key Responsibilities
Multi-ERP AI Strategy & Program Execution
  • Lead the end-to-end delivery roadmap for AI, machine learning, and advanced analytics initiatives across a hybrid ecosystem of modern SAP S/4HANA and legacy ERP systems
  • Manage schedules, milestones, dependencies, and resources for embedding intelligent technologies (e.g., SAP Business AI, custom cloud ML models) into diverse logistics and manufacturing workflows.
  • Orchestrate the deployment of predictive and generative AI models that harmonize data across fragmented systems to transform reactive workflows into unified, predictive operations.
  • Define and track program governance, agile delivery standards, and business ROI metrics for all data and AI deployments.

Data Harmonization & Integration Governance
  • Oversee the architectural orchestration of massive data volumes extracted from siloed legacy databases and SAP S/4HANA into unified cloud data platforms (e.g., SAP Datasphere, Snowflake, Databricks, AWS, or Azure).
  • Partner with data engineering teams to establish robust data cleansing, mapping, and harmonization pipelines, ensuring clean master data (materials, vendors, customers) across mismatched ERP platforms for AI model training.
  • Coordinate data extraction and ETL workflows across standard modules (e.g., SAP S/4HANA MM/SD/PP, legacy WMS, legacy TMS, and external IoT feeds).
  • Ensure hybrid data handling workflows comply with international logistics regulations, enterprise security policies, and global data privacy laws.

Stakeholder Alignment & Change Management
  • Serve as the central communication hub between executive supply chain leadership, legacy system technical teams, SAP functional analysts, and data science groups.
  • Translate highly complex data mapping, algorithmic methodologies, and hybrid architectural strategies into clear, value-driven business narratives for executive leadership.
  • Drive comprehensive change management and user-adoption frameworks to ensure plant, warehouse, and purchasing managers trust and adopt AI-driven recommendations despite underlying data fragmentation.
Technical Skills
  • ERP Landscape Expertise: Strong functional or technical familiarity with SAP S/4HANA core supply chain modules (MM, SD, PP) alongside an understanding of legacy transactional tables and relational databases.
  • Data Integration & Harmonization: Working knowledge of middleware, ETL/ELT pipelines, API frameworks, and cloud data ecosystems used to merge disparate data streams.
  • AI & Machine Learning: Foundational understanding of the machine learning lifecycle, predictive modeling, demand forecasting algorithms, or generative AI extensions for automated procurement and sourcing.
  • Methodologies: Expert mastery of Agile, Scrum, and SAP Activate or hybrid project deployment methodologies alongside delivery applications like Jira or Azure DevOps.

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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