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Privacy Preserving Machine Learning Jobs in Chicago, IL

This is not a software engineering, data science, or machine learning development role. Instead ... Promote AI as a productivity enhancement tool that augments employee capability while preserving ...

Quantitative Research Intern

Chicago, IL ยท On-site

$250K - $300K/yr

Formulate and apply mathematical modeling, quantitative methods and machine learning techniques to ... Privacy Notice for information about certain legal rights at #LI-DNI

We provide authenticated, privacy-enhanced data and analytics, innovative fit-for-purpose health ... You will work at the intersection of machine learning, experimentation,data engineering,and ...

Stay up to date with the latest trends in artificial intelligence, machine learning, and the ... Candidate Privacy Policy Orion Systems Integrators, LLC and its subsidiaries and its affiliates ...

Data Engineer

Chicago, IL ยท On-site

$118K - $141K/yr

... machine learning platforms Design and implement data access controls, identity management, and ... e.g., data integrity, privacy, and security controls) Cloud & AutomationDevelop and manage ...

Databricks Engineer

Chicago, IL ยท On-site

$118K - $141K/yr

... machine learning platforms Design and implement data access controls, identity management, and ... e.g., data integrity, privacy, and security controls) Cloud & AutomationDevelop and manage ...

We provide authenticated, privacy-enhanced data and analytics, innovative fit-for-purpose health ... You will work at the intersection of machine learning, experimentation,data engineering,and ...

TransUnion's Job Applicant Privacy Notice Personal Information We Collect Your Privacy Choices Team ... Experience in genAI-powered machine learning, such as agentic workflows, ontology designs, and ...

Customer Care Associate

Des Plaines, IL ยท On-site

$20 - $25/hr

Our core technology team includes leading minds in data science, embedded machine learning ... privacy requirements, and internal procedures What We're Looking For Required: Strong customer ...

Showing results 41-60

Privacy Preserving Machine Learning information

See Chicago, IL salary details

$102.5K

$119K

$133.4K

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 Chicago, IL is $118,987.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $132,900.00 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 are popular job titles related to Privacy Preserving Machine Learning jobs in Chicago, IL? For Privacy Preserving Machine Learning jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Privacy Preserving Machine Learning jobs in Chicago, IL look for? The top searched job categories for Privacy Preserving Machine Learning jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Privacy Preserving Machine Learning jobs? Cities near Chicago, IL with the most Privacy Preserving Machine Learning job openings:

Enterprise AI Enablement Lead

Jorie AI

Oak Brook, IL โ€ข On-site

Full-time

Re-posted 12 days ago


Job description

Position Summary

Jorie Healthcare Partners is seeking an Enterprise AI Enablement Lead to drive the responsible adoption of Artificial Intelligence technologies across the organization. This individual will serve as the organization's internal AI enablement expert, partnering with business units to identify opportunities where AI can improve productivity, reduce repetitive work, streamline business processes, and enhance employee effectiveness while maintaining information security, regulatory compliance, and appropriate human oversight.


This is not a software engineering, data science, or machine learning development role. Instead, this position serves as an internal consultant and strategic advisor, helping employees effectively adopt AI technologies through education, workflow consulting, process improvement, governance coordination, and organizational change management.

Working closely with Information Technology, Information Security, Compliance, Human Resources, Development, Revenue Cycle Management, and Operations, this individual will help ensure AI is introduced in a manner that improves employee effectiveness while preserving organizational knowledge, human expertise, regulatory compliance, and business continuity.

Core Responsibilities

Enterprise AI Enablement

  • Lead enterprise-wide AI adoption initiatives across business and technical departments.
  • Evaluate business processes to identify opportunities for AI-assisted productivity improvements.
  • Develop enterprise AI implementation playbooks, reusable workflow patterns, and department-specific adoption strategies.
  • Assist departments in determining when Artificial Intelligence, Robotic Process Automation (RPA), workflow automation, APIs, or traditional process improvements represent the most appropriate solution.
  • Promote AI as a productivity enhancement tool that augments employee capability while preserving critical business knowledge and decision-making.


Business Process Consulting

  • Conduct AI Opportunity Assessments with business leaders to identify repetitive work, knowledge-intensive activities, and workflow bottlenecks suitable for AI-assisted automation.
  • Analyze departmental workflows and recommend practical AI solutions that improve efficiency and business outcomes.
  • Design AI-enabled business workflows that improve operational effectiveness while preserving appropriate human oversight and accountability.
  • Partner with department leadership to prioritize AI initiatives based on business value, operational readiness, organizational impact, and regulatory considerations.
  • Facilitate workshops that help departments identify practical AI use cases and develop implementation roadmaps.


AI Education & Workforce Development

  • Develop and deliver enterprise AI education programs for technical and non-technical employees.
  • Deliver role-based AI enablement training tailored to departments including Development, Revenue Cycle Management, Operations, Finance, Human Resources, and Information Technology.
  • Teach effective prompting, AI verification techniques, responsible AI usage, AI limitations, and methods for validating AI-generated content.
  • Develop AI best practices that encourage employees to understand, validate, and appropriately apply AI-generated recommendations.
  • Maintain internal AI documentation, implementation standards, approved use-case libraries, and enterprise AI knowledge resources.
  • Provide ongoing AI coaching through workshops, office hours, and departmental consultations.

AI Standards & Governance Coordination

  • Partner with Information Security, Compliance, and Legal to operationalize enterprise AI standards.
  • Translate organizational policies, security standards, and regulatory requirements into practical AI implementation guidance.
  • Coordinate AI implementation reviews and risk assessments with appropriate governance stakeholders.
  • Assist with the development and maintenance of AI-related standards, procedures, and implementation guidance while ensuring policy ownership remains with the appropriate governance teams.
  • Maintain the organization's catalog of approved AI platforms, approved AI use cases, and enterprise AI implementation guidance.

Continuous Improvement & Innovation

  • Monitor emerging AI technologies applicable to healthcare operations and enterprise business functions.
  • Evaluate new AI capabilities for business value, security implications, regulatory alignment, and operational impact.
  • Measure AI adoption, productivity improvements, employee engagement, and organizational outcomes.
  • Track AI adoption metrics and business value to support continuous organizational improvement.
  • Recommend enhancements to AI-enabled business processes and enterprise AI strategy.
  • Identify opportunities to responsibly expand AI capabilities throughout the organization.


Required Qualifications

  • Bachelor's degree in Information Technology, Business Administration, Healthcare Administration, Business Process Improvement, Organizational Development, related discipline, or equivalent professional experience.
  • Five (5) or more years of experience in Information Technology, Digital Transformation, Business Process Improvement, Enterprise Applications, Automation, Healthcare Operations, or related disciplines.
  • Experience supporting organizations operating under HIPAA, HITRUST, NIST, FedRAMP, or comparable regulatory and security frameworks.
  • Strong understanding of healthcare privacy, cybersecurity, compliance, and enterprise governance principles.
  • Experience with enterprise AI platforms such as Microsoft Copilot, Azure OpenAI, ChatGPT Enterprise, or similar enterprise AI technologies.
  • Demonstrated experience facilitating organizational change, technology adoption, or business transformation initiatives.
  • Excellent presentation, facilitation, communication, consulting, and relationship management skills.


Preferred Qualifications

  • Experience implementing enterprise automation solutions including Robotic Process Automation (RPA), Microsoft Power Platform, workflow automation, or similar technologies.
  • Experience supporting healthcare Revenue Cycle Management operations.
  • Familiarity with Microsoft 365 Copilot, Azure AI Services, Power Platform, or enterprise AI ecosystems.
  • Experience leading enterprise technology adoption or organizational enablement initiatives.
  • Familiarity with HITRUST, HIPAA, FedRAMP, NIST CSF, ISO 27001, or comparable governance frameworks.
  • Lean Six Sigma, PMP, CBAP, Prosci Change Management, ITIL, or related professional certifications.

Success Measures

Success in this role will be measured by:

  • Safe, secure, and compliant enterprise AI adoption.
  • Increased employee productivity through AI-enabled workflows.
  • Reduction in repetitive manual work across business units.
  • Employee AI competency, adoption, and confidence.
  • Successful implementation of AI initiatives across multiple departments.
  • Development and adoption of enterprise AI standards, implementation playbooks, and reusable workflow patterns.
  • High employee satisfaction with AI education, consulting, and enablement services.
  • Strong collaboration with Information Technology, Security, Compliance, and business leadership.
  • Demonstrated business value through measurable operational improvements and responsible AI adoption.

Position Mission

Enable Jorie Healthcare Partners to responsibly adopt Artificial Intelligence by empowering employees, improving business processes, promoting responsible AI usage, and ensuring AI technologies are implemented securely, effectively, and in alignment with organizational policies, regulatory requirements, and long-term organizational capability.