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Differential Privacy Jobs in Texas (NOW HIRING)

Protopia AI

Applied Scientist

Austin, TX · On-site

Familiar with concepts in data privacy, such as differential privacy, secure multi-party computation, NLP red teaming, and homomorphic encryption.

Protopia AI

Applied Scientist

Austin, TX · On-site

Familiar with concepts in data privacy, such as differential privacy, secure multi-party computation, NLP red teaming, and homomorphic encryption.

Natera

Lab Assistant I

Austin, TX · On-site

$21/hr

Added 15% shift differential for Sat/Sun PRIMARY RESPONSIBILITIES: Assist licensed/certified staff ... privacy, General Policies and Procedure Compliance training and security training as soon as ...

Adecco

Forklift Operator

Fort Worth, TX

$17/hr

... shift differential pay for 2nd shift) Click on Apply Now to be considered for these Forklift ... To read our Candidate Privacy Information Statement, which explains how we will use your ...

Adecco

Forklift Operator

Fort Worth, TX

$17/hr

... shift differential pay for 2nd shift) Click on Apply Now to be considered for these Forklift ... To read our Candidate Privacy Information Statement, which explains how we will use your ...

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All JobsDifferential Privacy JobsDifferential Privacy Jobs in Texas

Differential Privacy information

What is differential privacy?

Differential privacy is a mathematical framework used to ensure that individual data remains private when analyzing and sharing aggregate information from a dataset. It introduces controlled random noise to the results of queries or computations, making it difficult to determine whether any specific individual's data is included. This helps organizations gain insights from data while providing strong privacy guarantees for individuals, even against attackers with access to other information. Differential privacy is widely used in fields such as statistics, machine learning, and data publishing.

What are some common challenges faced by professionals working in differential privacy roles?

Professionals in differential privacy often encounter challenges balancing data utility with privacy guarantees, as stricter privacy controls can limit the usefulness of data for analysis. They also need to stay updated on evolving privacy regulations and technological advancements. Collaboration with data scientists, engineers, and legal teams is essential to ensure solutions meet both technical and compliance requirements. Additionally, translating complex mathematical concepts into practical, scalable systems that integrate smoothly with existing infrastructure can be a significant hurdle.

What are the key skills and qualifications needed to thrive as a differential privacy engineer, and why are they important?

To thrive as a Differential Privacy Engineer, you need a strong background in mathematics, statistics, computer science, and experience with privacy-preserving algorithms, usually supported by an advanced degree. Familiarity with programming languages like Python or R, privacy frameworks (such as Google's DP library), and knowledge of data security regulations are typically required. Excellent problem-solving skills, attention to detail, and the ability to communicate complex concepts to non-experts are crucial soft skills. These competencies are vital to designing robust privacy solutions that protect user data while enabling meaningful data analysis.

What is the difference between Differential Privacy vs Data Scientist?

AspectDifferential PrivacyData Scientist
Primary FocusProtecting individual data privacy in datasetsAnalyzing and interpreting complex data to inform business decisions
Required SkillsMathematics, privacy algorithms, data securityStatistics, programming, data visualization
Work EnvironmentResearch labs, tech companies, privacy-focused organizationsBusiness, tech firms, consulting
CertificationsPrivacy certifications, data security credentialsData science certifications, programming skills

While Differential Privacy focuses on implementing privacy-preserving techniques in data handling, Data Scientists analyze data to extract insights. Both roles require strong technical skills, but their core objectives differ: one emphasizes privacy protection, the other data analysis.

What are popular job titles related to Differential Privacy jobs in Texas?

For Differential Privacy jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Differential Privacy jobs in Texas look for?

The top searched job categories for Differential Privacy jobs in Texas are:

What cities in Texas are hiring for Differential Privacy jobs?

Cities in Texas with the most Differential Privacy job openings:

Differential Privacy jobs near you
Infographic showing various Differential Privacy job openings in Texas as of August 2026, with employment types broken down into 100% Full Time. Highlights an 86% In-person, and 14% Remote job distribution.

Applied Scientist

Protopia AI

Austin, TX • On-site

Full-time

Posted 20 days ago

Job description

Applied Scientist

We are hiring an Applied Scientist with experience in performing hyperparameter optimizations, evaluating model performance, and deploying production natural language systems. Working with an elite group of professionals, you will have the opportunity to work hands on with ML research and development. This environment allows for vigorous dialogue on the problems needed to solve for and the opportunity to share bleeding edge solutions. Ultimately though, the role requires an individual who can commit to team conclusions as you work towards a common goal.

A skilled researcher, the successful candidate will develop novel methods to obfuscate data for common NLP tasks such as question/answering, instruction following, and sentiment analysis to enhance cutting-edge LLMs to preserve user privacy effectively. You will directly interface with Large Language Models (such as GPT, BLOOM, LaMDA, and LLaMA) and also with their core NLP privacy technology. You will also develop tools and metrics for handling machine learning experiments during training, inference, logging, and analytics. The successful candidate will also bring a deep understanding of transformer architecture, adversarial training knowledge.

Required:

  • Experience with deploying distributed systems for training deep learning models
  • Experience with developing NLP systems, specifically with language modeling.
  • Experience with fine-tuning Large Language Models (LLM) on external datasets.
  • Hands-on experience with using HuggingFace APIs.
  • 4 Years Experience with Python and 2 Years of Professional Experience with PyTorch, NumPy

Required

  • Ph.D./MS in Computer Science or Electrical and Computer Engineering, specializing in NLP and deep learning.
  • Speed optimization/ optimization of memory consumption for LLM
  • Proven ability to impact products with cutting-edge research technology.
  • Experience with downstream NLP models (includes question answering, sequence labeling, and downstream classification.)
  • Experience with using Kubernetes.
  • Experience training LLM's such as GPT, BERT, LaMDA, and LLaMA.
  • Comfort with fast R&D cycles (ideation through to deployment and production systems).
  • Familiar with concepts in data privacy, such as differential privacy, secure multi-party computation, NLP red teaming, and homomorphic encryption.

Apply