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Privacy Preserving Machine Learning Jobs in Sparta, NJ

Avis Budget Group

IT Audit Manager

Parsippany, NJ · On-site

... AI), machine learning, cloud computing, cybersecurity, third-party providers, and digital ... Understanding of data privacy regulations (GDPR, CCPA) and their IT control implications * Track ...

Avis Budget Group

IT Audit Manager

Parsippany, NJ · On-site

... AI), machine learning, cloud computing, cybersecurity, third-party providers, and digital ... Understanding of data privacy regulations (GDPR, CCPA) and their IT control implications * Track ...

Deloitte

Lead Forward Deployed Engineer - AWS

Morristown, NJ · On-site

$105K - $138K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ ... Familiarity with security, privacy, and compliance considerations The wage range for this role ...

Deloitte

Senior Forward Deployed Engineer- AWS

Morristown, NJ · On-site

$107K - $147K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ ... Familiarity with security, privacy, and compliance considerations The wage range for this role ...

Deloitte

Forward Deployed Engineer- AWS

Morristown, NJ · On-site

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ ... Familiarity with security, privacy, and compliance considerations The wage range for this role ...

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Showing results 21-40

All JobsPrivacy Preserving Machine Learning JobsPrivacy Preserving Machine Learning Jobs in Sparta, NJ

Privacy Preserving Machine Learning information

See Sparta, NJ salary details

$104.7K

$121.5K

$136.2K

How much do privacy preserving machine learning jobs pay per year?

As of Sep 3, 2026, the average yearly pay for privacy preserving machine learning in Sparta, NJ is $121,497.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,200.00 and $135,700.00 per year, depending on experience, location, and employer.

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 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 cities near Sparta, NJ are hiring for Privacy Preserving Machine Learning jobs?

Cities near Sparta, NJ 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 Sparta, NJ as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $121,497 per year, or $58.4 per hour.

Senior Enterprise AI Solution Architect

Brooksource

Parsippany, NJ • On-site

$140 - $160/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago

Job description

Senior Enterprise AI Solution Architect (Director Level)


Location: Parsippany, NJ

Schedule: (Onsite preferred, open to remote/traveling onsite 2x a month 3-4 days)

Employment Type: 3-months (possibility of extension)

Pay: $140-160/hr (W-2/40hrs a week)


Overview

Brooksource is seeking a highly accomplished Senior Enterprise AI Solution Architect (Director Level) to lead the strategy, architecture, and implementation of enterprise-scale Artificial Intelligence solutions for a global organization undergoing significant AI-driven transformation.

This is a highly visible leadership opportunity for a seasoned technology leader who can bridge executive strategy and technical execution. The ideal candidate will define enterprise AI architecture, establish AI governance frameworks, drive adoption of Generative AI and Agentic AI solutions, and partner with senior business and technology stakeholders to deliver measurable business outcomes.

The successful candidate will help shape the future of enterprise AI capabilities across areas including intelligent automation, digital operations, enterprise knowledge management, service management, and AI-powered productivity platforms.


Key Responsibilities

Enterprise AI Strategy & Transformation

  • Define and evolve enterprise AI, Generative AI, and Agentic AI strategies and roadmaps.
  • Establish AI reference architectures, standards, and best practices across the organization.
  • Identify, prioritize, and deliver high-value AI use cases in partnership with business and technology leaders.
  • Lead enterprise-wide AI transformation initiatives and strategic programs.
  • Develop business cases, ROI frameworks, and value realization models for AI investments.
  • Serve as a trusted advisor to executive leadership on emerging AI technologies and industry trends.

Solution Architecture & Design

  • Architect enterprise-scale AI solutions leveraging Generative AI, Agentic AI, Multi-Agent Systems, Conversational AI, and Voice AI.
  • Design secure, scalable, resilient, and cloud-native architectures.
  • Define architecture patterns for:
  • AI Agent Platforms
  • Multi-Agent Orchestration
  • Enterprise RAG Solutions
  • Knowledge Intelligence Platforms
  • Semantic Search
  • Intelligent Automation
  • AI-Enhanced Service Management
  • Conversational and Voice-Based Solutions
  • Provide technical leadership through architecture reviews and governance processes.

AI Platform & Technology Leadership

  • Define enterprise AI platforms, operating models, and governance standards.
  • Architect and govern modern AI ecosystems utilizing technologies such as:
  • Microsoft Azure AI Services
  • Azure OpenAI
  • Microsoft AI Foundry
  • Microsoft Copilot
  • Azure AI Search
  • Vector Databases
  • Semantic Kernel
  • LangChain
  • AutoGen
  • CrewAI
  • LLMOps and MLOps Platforms
  • Ensure AI solutions are scalable, observable, maintainable, and aligned with operational excellence objectives.

Enterprise Integration & Automation

  • Design integrations across complex enterprise technology environments.
  • Establish API strategies and integration patterns that enable successful AI adoption.
  • Drive automation and orchestration initiatives that improve efficiency and business outcomes.
  • Collaborate with enterprise application, infrastructure, and operations teams to deliver connected AI solutions.

Governance, Security & Responsible AI

  • Define and implement enterprise AI governance frameworks.
  • Ensure adherence to security, privacy, legal, regulatory, and compliance requirements.
  • Partner with security and risk organizations to establish AI guardrails and controls.
  • Develop standards for:
  • Responsible AI
  • AI Security
  • Model Governance
  • Prompt Governance
  • Data Privacy
  • Risk Management
  • Explainability
  • Auditability

Innovation & Leadership

  • Evaluate emerging AI technologies, platforms, tools, and vendors.
  • Lead proofs-of-concept, pilots, and innovation initiatives.
  • Create future-state architecture roadmaps aligned with organizational strategies.
  • Mentor architects, engineers, and technology teams on AI best practices.
  • Represent the organization in executive discussions, industry forums, and strategic partner engagements.


Required Qualifications

Education & Experience

  • Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
  • Master's degree in Technology, Artificial Intelligence, Data Science, Business Administration, or related discipline preferred.
  • 18+ years of overall technology experience.
  • 12+ years in Enterprise Architecture, Solution Architecture, Digital Transformation, or similar leadership roles.
  • 5+ years designing and implementing AI, Machine Learning, Generative AI, or Data Platform solutions.
  • Proven success delivering large-scale enterprise AI initiatives.
  • Experience driving enterprise transformation programs and strategic technology adoption.
  • Strong background working with executive leadership and global stakeholders.


Technical Expertise

Artificial Intelligence & Generative AI

  • Generative AI
  • Agentic AI
  • Multi-Agent Systems
  • Retrieval-Augmented Generation (RAG)
  • Large Language Models (LLMs)
  • Prompt Engineering
  • AI Agents
  • Conversational AI
  • Voice AI

Cloud & Platform Technologies

  • Microsoft Azure
  • Azure OpenAI
  • Azure AI Services
  • Microsoft AI Foundry
  • Azure AI Search
  • Azure Kubernetes Services (AKS)
  • Cloud-Native Architecture

Software Development & Engineering

  • Python
  • REST APIs
  • Microservices
  • Containers
  • Kubernetes
  • GitHub
  • Azure DevOps

AI Operations & Data Platforms

  • LLMOps
  • MLOps
  • Data Architecture
  • Vector Databases
  • Knowledge Graphs
  • AI Observability
  • Monitoring & Telemetry

AI Frameworks & Orchestration

  • Semantic Kernel
  • LangChain
  • AutoGen
  • CrewAI
  • Prompt Flow
  • AI Evaluation Frameworks


Leadership Competencies

  • Executive-level communication and presentation skills
  • Strategic thinking and enterprise mindset
  • Ability to influence senior leadership and executive stakeholders
  • Strong stakeholder management capabilities
  • Business-focused approach to technology investment and value realization
  • Vendor and partner management expertise
  • Innovation leadership and change management
  • Team development, mentorship, and coaching experience
  • Ability to operate effectively from executive strategy discussions to detailed architecture reviews


Preferred Certifications

  • AI Architecture Certifications
  • Data Architecture Certifications
  • TOGAF
  • Azure Solutions Architect Expert
  • AWS or GCP Cloud Architecture Certifications
  • PMP
  • Agile Certifications
  • SAFe Certifications


Disclaimer: Brooksource, Medasource, and Calculated Hire are part of the Eight Eleven Group family of companies and operate under Eight Eleven Group, LLC. All employees receive the same benefits, policies, and terms of employment.

EEO: We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, ancestry, age, disability, genetic information, marital status, military or veteran status, citizenship, pregnancy (including childbirth, lactation, and related conditions), or any other protected status in accordance with applicable federal, state, and local laws.

Benefits & Perks: Brooksource offers competitive medical, dental, vision, Health Savings Account, Dependent Care FSA, and supplemental coverage with plans that can fit each employee’s needs. We offer a 401k plan that includes a company match and is fully vested after you become eligible, paid time off, sick time, and paid company holidays. We also offer an Employee Assistance Program (EAP) that provides services like virtual counseling, financial services, legal services, life coaching, etc.

Pay Disclaimer: The pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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