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Privacy Preserving Machine Learning Jobs in Georgia

Omnissa

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$162K - $342K/yr

These practices are applied thoughtfully and with respectforcandidate privacy. What is the ... As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems ...

Career Renew

Senior Machine Learning Engineer

Atlanta, GA · Remote

$165K - $225K/yr

Our solutions deliver diagnostic-quality results in minutes while preserving tissue samples for ... The ideal candidate will have deep expertise in Machine Learning and building generalizable ...

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

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

FanDuel

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

As a Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast ... Data security and privacy (e.g. GDPR, CPP) * Data governance and data testing frameworks

FanDuel

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

As a Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast ... Data security and privacy (e.g. GDPR, CPP) * Data governance and data testing frameworks

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All JobsPrivacy Preserving Machine Learning JobsPrivacy Preserving Machine Learning Jobs in Georgia

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 Georgia look for? The top searched job categories for Privacy Preserving Machine Learning jobs in Georgia are:
What cities in Georgia are hiring for Privacy Preserving Machine Learning jobs? Cities in Georgia with the most Privacy Preserving Machine Learning job openings:
Privacy Preserving Machine Learning jobs near you
Infographic showing various Privacy Preserving Machine Learning job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer III 4P/791

4P Consulting Inc.

Atlanta, GA

Contractor

Posted 11 days ago

Job description

Position: Machine Learning Engineer III – AI/ML Product Engineering

Location: Atlanta, GA

Duration: 5 Months
Client: Southern Company Services

Southern Company Services is seeking an experienced Machine Learning Engineer III to develop scalable, reusable, and production-grade AI products for deployment across multiple operating companies.

This role will focus on Retrieval-Augmented Generation, multi-agent systems, natural language processing, model deployment, and cloud-based AI solutions. The ideal candidate will have strong software engineering skills, hands-on AI/ML experience, and expertise with Azure or Google Cloud Platform.

Key Responsibilities

· Design and build modular, reusable AI components and services.

· Develop scalable RAG solutions using structured and unstructured data.

· Engineer multi-agent systems for task coordination, workflow automation, and decision support.

· Build transcription and NLP pipelines for customer-interaction analysis.

· Develop and fine-tune models using PyTorch, Hugging Face Transformers, LangChain, or similar frameworks.

· Package and deploy models using Azure Machine Learning, Google Cloud Platform, or Databricks.

· Integrate Databricks for data ingestion, feature engineering, experimentation, and model development.

· Develop reusable libraries, APIs, templates, and engineering patterns.

· Partner with MLOps, DevOps, data engineering, architecture, and product teams.

· Implement monitoring for model performance, data drift, system usage, and operational reliability.

· Ensure AI solutions meet enterprise security, privacy, compliance, scalability, and observability requirements.

· Provide technical guidance to teams adopting shared AI products and components.

Required Qualifications

· Strong experience developing and deploying production-grade AI and machine learning solutions.

· Hands-on experience with RAG architectures, LLM applications, multi-agent systems, and NLP.

· Experience with Azure AI services, Google Cloud Platform AI services, or Azure Machine Learning.

· Proficiency with Python and frameworks such as PyTorch, Transformers, or LangChain.

· Experience deploying scalable models and AI services in cloud environments.

· Knowledge of APIs, software engineering practices, model monitoring, and MLOps.

· Experience working with structured and unstructured datasets.

· Strong communication, collaboration, analytical, and problem-solving skills.

Preferred Qualifications

· Experience with Databricks, vector databases, embeddings, and semantic search.

· Experience building reusable enterprise AI platforms or shared AI services.

· Knowledge of model evaluation, data drift, observability, and responsible AI.

· Familiarity with CI/CD, containers, Kubernetes, and cloud-native deployment.

· Utility, energy, or regulated-industry experience is preferred.