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Privacy Preserving Machine Learning Jobs in Oregon

Upstart

Senior Manager, Privacy Engineering

OR · On-site +1

$100K - $128K/yr

The team works across Engineering, Security, Legal, Compliance, Product, Data, and Machine Learning to embed privacy-by-design into how Upstart builds, uses, retains, and governs data. As the Senior ...

Aptive

Minimum Qualifications Minimum 8 years of professional experience in data science, machine learning ... privacy-preserving ML techniques (e.g., differential privacy, federated learning) applied to ...

Upstart

Senior Privacy Engineer

OR · On-site +1

$104K - $143K/yr

The team works across Engineering, Security, Legal, Compliance, Product, Data, and Machine Learning to make privacy-by-design practical and scalable. As a Privacy Engineer II at Upstart, you will ...

Quora

$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

Quora

$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

Quora

$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

Intel

Sr. Machine Learning Engineer

Hillsboro, OR

$113K - $156K/yr

... human privacy by design. We believe transformative AI should have a positive impact on people ... Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research ...

OneStudyTeam

Senior Data Scientist

OR · On-site +1

$140K - $190K/yr

... machine learning algorithms to improve patient enrollment and trial management. You'll work in a highly regulated healthcare data environment, ensuring compliance with privacy standards while ...

Netflix

OR · On-site

$466K - $750K/yr

... privacy, and anonymization. Responsibilities Apply modeling and machine learning techniques to business problems at the intersection of product and data science Autonomously identify and pursue ...

New

EM Key Solutions Inc

Temporary AI Engineer

OR · On-site +1

Ensure all AI solutions comply with VA cybersecurity, privacy, accessibility, and Trustworthy AI ... Experience with Azure AI Studio, Azure Machine Learning, vector databases, and prompt engineering.

EM Key Solutions Inc

AI Engineer

OR · On-site +1

Ensure all AI solutions comply with VA cybersecurity, privacy, accessibility, and Trustworthy AI ... Experience with Azure AI Studio, Azure Machine Learning, vector databases, and prompt engineering.

Cornerstone

$114K - $137K/yr

Ensure data accuracy, integrity, privacy, security, and compliance through quality control ... Experience building and deploying machine learning models in production. Strong proficiency in ...

Cornerstone OnDemand

$114K - $137K/yr

Ensure data accuracy, integrity, privacy, security, and compliance through quality control ... Experience building and deploying machine learning models in production. Strong proficiency in ...

LMI

Artificial Intelligence Lead

AI capabilities are designed to provide decision support and transparency while preserving human ... Advanced knowledge of AI, machine learning, deep learning, and data science concepts (Master's or ...

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All JobsPrivacy Preserving Machine Learning JobsPrivacy Preserving Machine Learning Jobs in Oregon

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 Oregon look for? The top searched job categories for Privacy Preserving Machine Learning jobs in Oregon are:
What cities in Oregon are hiring for Privacy Preserving Machine Learning jobs? Cities in Oregon with the most Privacy Preserving Machine Learning job openings:
Privacy Preserving Machine Learning jobs near you

Senior Manager, Privacy Engineering

Upstart

OR • On-site, Remote

$100K - $128K/yr

Full-time

Re-posted 11 days ago

Upstart rating

7.6

Company rating: 7.6 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

Job description

The Team

Upstart's Privacy Engineering team builds the systems, controls, and practices that help protect borrower, applicant, partner, and Upstarter data across our products and platforms. The team works across Engineering, Security, Legal, Compliance, Product, Data, and Machine Learning to embed privacy-by-design into how Upstart builds, uses, retains, and governs data.
As the Senior Manager, Privacy Engineering at Upstart, you will lead the team responsible for building scalable privacy infrastructure and technical privacy controls across Upstart's AI lending marketplace. You will set the team's roadmap, grow and support privacy engineers, and help translate privacy and regulatory requirements into durable engineering systems.


How you'll make an impact

  • Lead the Privacy Engineering team's strategy, roadmap, and execution across privacy infrastructure, data governance, and privacy-by-design initiatives
  • Hire, coach, and develop a team of privacy engineers while establishing clear operating rhythms, priorities, and technical standards
  • Guide the design and delivery of scalable privacy controls, including data discovery, classification, access controls, audit logging, retention, deletion, lineage, encryption, and key management
  • Partner with Legal, Compliance, Security, Product, Data, Machine Learning, and Infrastructure teams to translate privacy requirements into practical technical solutions
  • Oversee privacy reviews, technical risk assessments, and threat modeling for new products, data flows, models, and platform capabilities
  • Define metrics and communicate progress, tradeoffs, dependencies, and risks to technical and cross-functional stakeholder

Minimum Qualifications

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience, and 8+ years of experience in engineering, including at least 3 years of direct people management experience
  • Experience leading engineering teams responsible for production software, platform, privacy, security, or data systems
  • Experience designing, building, or operating privacy, security, data governance, or data platform capabilities in production environments
  • Experience translating privacy, security, compliance, or regulatory requirements into technical controls
  • Experience working with cross-functional partners such as Legal, Compliance, Security, Product, Data, or Machine Learning teams

Preferred Qualifications

  • Knowledge of privacy-by-design principles, data minimization, purpose limitation, consent, retention, deletion, and data subject rights
  • Knowledge of privacy and data protection regulations or frameworks such as GDPR, CCPA/CPRA, GLBA, FCRA, or similar requirements
  • Experience with privacy reviews, threat modeling, risk assessments, data inventories, lineage systems, or automated policy enforcement
  • Experience building privacy or governance controls for machine learning, AI, financial services, lending, or other regulated data environments
  • Ability to communicate technical privacy tradeoffs clearly across engineering, legal, product, security, and business audiences

Travel requirements As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions' cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.

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