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Privacy Preserving Machine Learning Jobs in Georgia

RITWIK Infotech Inc

AI Architect

Atlanta, GA · On-site

$60.50 - $79.75/hr

Ensure AI solutions comply with healthcare security, privacy, and regulatory standards. * Establish ... Strong knowledge of Machine Learning, Deep Learning, NLP, Computer Vision, and Generative AI.

Adecco

Machine Operator

Braselton, GA

$19/hr

This is a great opportunity to further your existing skills as a Machine Operator, while learning ... To read our Candidate Privacy Information Statement, which explains how we will use your ...

Adecco

Machine Operator

Cumming, GA · On-site

$22/hr

... while learning new ones to assist you in your career. The best part is you would be joining a ... To read our Candidate Privacy Information Statement, which explains how we will use your ...

Primerica

Enterprise Data Security Architect

Duluth, GA

$180K - $250K/yr

Collaborate with data engineering teams to embed privacy-preserving techniques (differential privacy, federated learning, secure multi-party computation) where appropriate. * Command the ability to ...

Dolby

Senior Database Researcher

Atlanta, GA · On-site

... privacy. Key Responsibilities: * Investigate heterogenous data management techniques and polystore systems, including the application of AI & machine learning techniques to foundational data ...

Dolby

Sr. Data Researcher Engineer

Atlanta, GA · On-site

... privacy. Key Responsibilities * Investigate heterogenous data management techniques and polystore systems, including the application of AI & machine learning techniques to foundational data ...

Omnissa

Senior Data Scientist

Atlanta, GA · On-site +1

$146K - $304K/yr

These practices are applied thoughtfully and with respectforcandidate privacy. What is the ... Work with engineers to design and implement scalable machine learning pipelines, covering all ...

Adecco

Machine Operator (3rd shift)

Braselton, GA

$19.50/hr

... while learning new ones to assist you in your career. The best part is you would be joining a ... To read our Candidate Privacy Information Statement, which explains how we will use your ...

Trella Health

AI & Machine Learning * Build and scale the organization's AI/ML capabilities, including ... Governance, Privacy & Compliance * Own data governance, master data management, data quality, and ...

Manhattan Associates

Principal AI Engineer

Atlanta, GA · On-site

... privacy, and regulatory compliance. • Improve model accuracy, efficiency, scalability, and ... Machine Learning (classification, regression, clustering, recommendation systems), Deep Learning ...

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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.

AI Architect

RITWIK Infotech Inc

Atlanta, GA • On-site

$60.50 - $79.75/hr

Other

Posted 12 days ago

Job description

Role:AI Architect with Healthcare Background
Location: Atlanta,GA
Duration: contract
Job Summary
We are seeking an experienced AI Architect with a strong healthcare background to design, develop, and implement enterprise-grade AI and Machine Learning solutions that improve clinical, operational, and business outcomes. The ideal candidate will have expertise in AI/ML technologies, cloud platforms, healthcare interoperability standards, and regulatory compliance, with experience delivering AI solutions in healthcare environments. Key Responsibilities
  • Design and implement scalable AI/ML architectures for healthcare applications.
  • Collaborate with clinical, business, and IT stakeholders to identify AI use cases and solution strategies.
  • Develop AI-powered solutions for clinical decision support, predictive analytics, medical imaging, patient engagement, and operational efficiency.
  • Build and deploy Generative AI, NLP, and Large Language Model (LLM) solutions for healthcare workflows.
  • Design data pipelines for structured and unstructured healthcare data.
  • Integrate AI solutions with EHR/EMR systems and healthcare applications.
  • Ensure AI solutions comply with healthcare security, privacy, and regulatory standards.
  • Establish MLOps processes for model deployment, monitoring, governance, and lifecycle management.
  • Evaluate emerging AI technologies and recommend best practices.
  • Lead architecture reviews, proof-of-concepts, and enterprise AI initiatives.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Healthcare Informatics, or a related field.
  • 8+ years of experience in software engineering, AI/ML, cloud architecture, or solution architecture.
  • 3+ years of experience architecting AI solutions within the healthcare industry.
  • Strong knowledge of Machine Learning, Deep Learning, NLP, Computer Vision, and Generative AI.
  • Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and AI agents.
  • Hands-on experience with Python, SQL, and AI frameworks such as TensorFlow, PyTorch, LangChain, Hugging Face, or similar.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Experience deploying AI solutions using Kubernetes, Docker, and MLOps tools.
Healthcare Domain Expertise
  • Experience working with Electronic Health Records (EHR/EMR) systems such as Epic, Cerner, or Meditech.
  • Strong understanding of healthcare interoperability standards including HL7, FHIR, CDA, and DICOM.
  • Knowledge of healthcare regulations including HIPAA, HITECH, and data privacy/security best practices.
  • Experience with clinical data, claims data, population health, or value-based care initiatives.
Preferred Skills
  • Experience with Azure OpenAI, OpenAI APIs, Google Vertex AI, or Amazon Bedrock.
  • Knowledge of vector databases such as Pinecone, Weaviate, Chroma, or Milvus.
  • Experience with data engineering platforms such as Databricks, Snowflake, Spark, or Kafka.
  • Familiarity with DevOps, CI/CD, Infrastructure as Code (Terraform), and monitoring tools.
  • Strong communication, leadership, and stakeholder management skills.
Preferred Certifications
  • AWS Certified Solutions Architect
  • Microsoft Azure AI Engineer Associate
  • Google Professional Machine Learning Engineer
  • Healthcare-related certifications (preferred)
Desired Experience
  • 10+ years of IT experience with 5+ years in AI architecture.
  • Proven experience leading enterprise AI transformation initiatives in healthcare.
  • Experience delivering scalable, secure, and compliant AI platforms for hospitals, health systems, payers, or life sciences organizations.

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