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Privacy Preserving Machine Learning Jobs in Dallas, TX

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together ... You will build quantitative and machine learning solutions designed to reduce fraud losses ...

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

New

AI Engineering Associate Director

Plano, TX ยท On-site

$151.40 - $202.50/hr

Collaborate with security, privacy, legal, compliance, and architecture teams to ensure AI ... Handsโ€‘on experience building AI, machine learning, generative AI, analytics, automation, or ...

Senior Data Scientist

Frisco, TX ยท On-site

$128 - $180/hr

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together ... Develop, implement, and continuously improve machine learning and statistical models that support ...

... Machine Learning, MLflow, Azure AI Search, OpenAI/GenAI, Python, and SQL , driving 98-99 ... Knowledge of data privacy and document-retention requirements. Success Measures 99% exact-match ...

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... of machine learning/statistical models and ensure best performance Work closely with machine ... Consistent with Judge's Privacy Policy, information obtained from your consent will not be shared ...

Showing results 21-40

Privacy Preserving Machine Learning information

See Dallas, TX salary details

$98.4K

$114.3K

$128.1K

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 Dallas, TX is $114,261.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,900.00 and $127,600.00 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 Dallas, TX? For Privacy Preserving Machine Learning jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Privacy Preserving Machine Learning jobs in Dallas, TX look for? The top searched job categories for Privacy Preserving Machine Learning jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Privacy Preserving Machine Learning jobs? Cities near Dallas, TX with the most Privacy Preserving Machine Learning job openings:

Sr Data Scientist

Pinnacle Technical Resources

Fort Worth, TX โ€ข On-site

$90 - $100/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted yesterday

New


Job description

Job Title: Data Scientist โ€“ Machine Learning & Generative AI Location: Fort Worth, TX 76155 (Hybrid) Durations: 6-12+ Months with possible extension and conversions. Job Overview: We are seeking a Data Scientist to support the Service Recovery Modernization initiative. This resource will be embedded within the project team and will take ownership of the end-to-end development of machine learning and Generative AI solutions. The ideal candidate will have strong experience in data preparation, data pipeline development, machine learning, and deploying AI applications into production. Required: Experience working as a Data Scientist, Machine Learning Engineer, or in a similar role. Strong experience with data preparation, cleansing, transformation, and feature engineering. Hands-on experience designing and developing data pipelines. Strong programming skills in Python and SQL. Experience developing, testing, and deploying machine learning models. Experience building Generative AI or large language model applications. Understanding of the complete ML lifecycle, including development, validation, deployment, and monitoring. Experience working with structured and unstructured datasets. Preferred: Experience with cloud platforms such as AWS, Azure, or Google Cloud. Experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch. Knowledge of LLM orchestration, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation. Experience with MLOps tools, CI/CD pipelines, model monitoring, and containerized deployment. Experience delivering AI solutions for customer service, operational recovery, or process modernization initiatives. Familiarity with data governance, model governance, and responsible AI practices. Responsibilities: Work closely with the Service Recovery Modernization team to understand business needs and identify AI and machine learning opportunities. Collect, clean, transform, and prepare structured and unstructured data for analysis and modeling. Design, build, and maintain reliable data pipelines for ML and Generative AI applications. Develop, train, test, and validate machine learning models. Design and develop Generative AI applications using large language models. Deploy ML and GenAI solutions into production environments. Monitor model performance, accuracy, reliability, and data quality. Troubleshoot data, pipeline, and model-related issues. Collaborate with data engineers, software engineers, product owners, and business stakeholders. Document data processes, model designs, testing results, and deployment procedures. Follow security, privacy, governance, and responsible AI standards Pay Range: $90 - $100 The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global do not respond or click on any links. Instead, contact us directly at +1 214-740-2424. To report any concerns, please email us at legal@pinnacle1.com During the hiring process, we may use artificial intelligence (AI) tools to assist in evaluating information related to your application. These tools may help analyze job-related qualifications or assist recruiters in reviewing applications and interview responses. AI-generated information is one factor considered in our hiring process. Final employment decisions are made by qualified hiring personnel and are not based solely on AI-generated recommendations. #LI-NP4