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Privacy Preserving Machine Learning Jobs in Minnesota

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Job Applicant Privacy Notice: LI-SS2 LI-REMOTE

The Data Scientist II leverages machine learning and Generative AI (LLMs) to deliver scalable, data ... Support ethical AI practices, data privacy requirements, and governance standards. * Mentor junior ...

Posted today

Develop supervised and unsupervised machine learning solutions, including classification ... Experience with AI governance, Responsible AI, model risk, data ethics, privacy, security ...

New

We're looking for a Principal Machine Learning Engineer to build AI features for the family ... Ensure ethical standards and data privacy compliance in AI solutions. * Provide specialized AI/ML ...

We're looking for a Principal Machine Learning Engineer to build AI features for the family ... Ensure ethical standards and data privacy compliance in AI solutions. * Provide specialized AI/ML ...

Senior Data Scientist III

Minneapolis, MN · On-site

$115K - $192K/yr

You would apply machine learning and AI technologies to execute analytical and statistical projects ... Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified ...

Staying abreast of the latest advancements in AI and machine learning will be crucial for ... Knowledge of data governance, privacy practices, and Responsible AI principles.

Staying abreast of the latest advancements in AI and machine learning will be crucial for ... Knowledge of data governance, privacy practices, and Responsible AI principles.

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Showing results 1-20

Privacy Preserving Machine Learning information

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 Minnesota look for? The top searched job categories for Privacy Preserving Machine Learning jobs in Minnesota are:
Infographic showing various Privacy Preserving Machine Learning job openings in Minnesota as of June 2026, with employment types broken down into 33% Full Time, 65% Part Time, 1% Temporary, and 1% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution.

Director, Enterprise Capabilities Architect - Digital Transformation, AI, and Database

Peraton

Virginia, MN • On-site

$180 - $240/hr

Other

Posted 7 days ago


Peraton rating

8.3

Company rating: 8.3 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

49th of 223 rated it services


Job description

Required Qualifications:

  • 16+ years of industry experience
  • Deep expertise in AI/ML platform architecture including model development, training, and deployment pipelines, with demonstrated experience integrating AI and generative AI capabilities into enterprise or mission applications
  • Proven experience designing and implementing modern data platform architectures including data lakes, data mesh, and data fabric, with strong command of data governance, data quality, and data management frameworks in a federal environment
  • Demonstrated experience with MLOps practices and AI lifecycle management, from development and testing through production deployment and continuous monitoring
  • Demonstrated experience with Data Management Body of Knowledge (DMBoK), Data Management Capability Assessment Models (DCAM), Findable, Accessible, Interoperable, and Reusable (FAIR) Data Principles, and/or Control Objectives for Information and Related Technologies (COBIT)
  • Working knowledge of legacy system modernization strategies, application migration approaches, and API-first and microservices-based architecture patterns that accelerate digital transformation
  • Demonstrated experience applying human-centered design principles and iterative user research methods to federal digital transformation programs, with measurable outcomes in user adoption and mission effectiveness
  • Direct experience supporting federal government customers in a contractor environment, with a working understanding of mission requirements, acquisition processes, and the competitive federal market
  • Proven experience contributing to competitive federal pursuits, including technical solution development, architecture design, or competitive positioning in support of capture or proposal efforts
  • Demonstrated ability to translate complex AI, data, and digital transformation concepts into compelling solution narratives for capture teams, executive leadership, and government evaluators
  • A demonstrated bias for action and a track record of delivering technical work that contributed directly to competitive wins.
  • US citizenship and ability to obtain a Top Secret security clearance

Desired Qualifications:

  • Active TS/SCI with Polygraph eligibility
  • Direct experience in capture management, proposal development, or technical volume leadership on large-scale, competitive federal digital transformation or AI/Data bids
  • Familiarity with Responsible AI and algorithmic accountability frameworks aligned to OMB AI policy and Executive Order 14110, including experience applying AI ethics and bias mitigation practices in federal program contexts
  • Experience with federated learning and privacy-preserving AI techniques for sensitive or classified data environments where centralized model training is not feasible
  • Working knowledge of AI-ready data infrastructure including vector database architecture and retrieval-augmented generation (RAG) frameworks supporting large language model deployment in federal environments
  • Experience with synthetic data generation techniques for AI model training in data-scarce or operationally sensitive federal environments
  • Familiarity with edge AI and on-device inference architectures supporting disconnected, intermittent, or contested operational environments
  • Experience with digital twin modeling applied to mission systems, infrastructure, or operational environments
  • Familiarity with multimodal AI architectures integrating text, imagery, signals, and sensor data for mission applications
  • Experience presenting AI/Data strategies and digital transformation roadmaps directly to senior government customers or evaluators
  • Prior experience developing competitive positioning materials, technical discriminators, or solution playbooks that supported pursuit efforts in the federal AI or digital transformation market
  • Relevant certifications such as AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, Azure AI Engineer, or relevant data architecture and governance certifications (e.g, CDMP)

Peraton is looking for a Director, Digital Transformation, AI, and Data Architect to join the Corporate Growth, Enterprise Capabilities and Solutions team as one of the technical leads behind our most competitive pursuits. You will provide thought leadership and design differentiated service offerings, architectures, and technical strategies for digital modernization, artificial intelligence, and data-driven mission outcomes. These provide the people and process elements to the Peraton Labs technology developments. You will work directly alongside capture teams, growth leaders, sector CTOs, and technical SMEs from early strategic opportunity shaping through proposal submission to build solutions that win contracts and frameworks that make winning repeatable. If you are energized by high-stakes technical challenges and want to see your work translate directly into contract wins, this role was built for you.

What you’ll do:

  • Lead the Peraton Enterprise Capabilities and Solutions Portfolio for Digital Modernization, Artificial Intelligence, and Data from strategy through execution, ensuring every offering is aligned to business priorities, technically sound, and built to compete across all Peraton customer’s market spaces.
  • Work directly with capture teams, sector growth leaders, and SMEs to shape Digital Transformation and AI/Data solutions from early opportunity identification through proposal submission.
  • Develop technical discriminators, solution narratives, and competitive positioning materials that support capture and proposal efforts across the enterprise, with deep credibility in digital modernization, AI/ML architecture, and data platform design.
  • Design and develop scalable, reusable digital transformation and AI/Data service offerings, architectures, and technical frameworks that give Peraton's sector teams a competitive edge on federal pursuits.
  • Continuously evolve the portfolio by analyzing capability gaps, technology readiness, and market trends across federal digital modernization and AI adoption to identify portfolio enhancements and competitive differentiation opportunities that strengthen Peraton's position in core markets.
  • Provide thought leadership and author white papers and other solution artifacts to support customer engagement efforts highlighting newly developed frameworks and Peraton Labs applicable technologies.
  • Partner with sector growth teams, business stakeholders, and engineering leadership to translate market opportunities into viable, differentiated service offerings.
  • Drive the design and architecture of services across the portfolio. Ensure each service is fully defined with supporting sales assets, cost models, and solution guides that equip sector teams to sell and deliver.
  • Present technical strategies, AI/Data architecture roadmaps, and digital modernization solution recommendations to customers, capture teams, and executive leadership with the clarity and confidence to drive decisions.
  • Engage with key customers, industry partners, and technology vendors to stay ahead of evolving federal AI policy, emerging data platform capabilities, and competitive dynamics in Peraton's target markets.
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What Peraton employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Peraton

Sourced by ZipRecruiter

At Peraton, we re at the forefront of delivering the next big thing every day. We re the partner of choice to help solve some of the world s most daunting challenges, delivering bold, new solutions to keep people around the world safer and more secure.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Herndon, VA, US

Year founded

2017