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Privacy Preserving Machine Learning Jobs in Newark, NJ

Wells Fargo

Senior Specialty Protocol Engineer

Iselin, NJ · On-site

$106K - $145K/yr

Implement and optimize privacy-preserving primitives, specifically Pedersen Commitments and ... State Machine Design: Design a customKVStorestate machine that manages homomorphic encrypted ...

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Privacy Preserving Machine Learning information

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$104K

$120.8K

$135.4K

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 Newark, NJ is $120,786.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,600.00 and $134,900.00 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 Newark, NJ? For Privacy Preserving Machine Learning jobs in Newark, NJ, the most frequently searched job titles are:
What job categories do people searching Privacy Preserving Machine Learning jobs in Newark, NJ look for? The top searched job categories for Privacy Preserving Machine Learning jobs in Newark, NJ are:
What cities near Newark, NJ are hiring for Privacy Preserving Machine Learning jobs? Cities near Newark, 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 Newark, NJ as of June 2026, with employment types broken down into 77% Full Time, 20% Part Time, and 3% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $120,786 per year, or $58.1 per hour.

Senior Machine Learning Engineer - Healthcare

Stone Alliance Group Career Page

New York, NY • On-site, Remote

$118K - $148K/yr

Full-time

Medical, Retirement

Re-posted 5 days ago

Job description

Our client is seeking an Senior Machine Learning Engineer to join their Center for Data Analytics, Innovation, and Rigor (DAIR) team in New York City.

As the Senior Machine Learning (ML) Engineer, you will apply expertise in Natural Language Processing (NLP) and Large Language Models (LLMs) to develop and implement innovative ML solutions that have the potential to make a significant impact in the lives of children and adolescents struggling with mental health issues. You will work with researchers, clinicians, and software engineers within DAIR and across departments to design, prototype, deploy and maintain applied ML solutions to enhance our digital mental health tools.

This position is based in a professional office environment. It requires the ability to sit or stand for extended periods, operate standard office equipment (including computers, phones, copiers, and printers), perform repetitive tasks, and communicate effectively with others. Occasional lifting of up to 10 pounds may also be required. This role may require occasional travel for meetings.

Our client is dedicated to transforming the lives of children and families struggling with mental health and learning disorders by giving them the help they need. They have become the leading independent nonprofit in children's mental health by providing gold-standard evidence-based care, delivering educational resources to millions of families each year, training educators in underserved communities, and developing tomorrow's breakthrough treatments.

Responsibilities:

- Design, implement, and maintain machine learning models with a focus on NLP and LLMs for real-world application in the mental health field.

- Perform analyses on large datasets using high-performance computing infrastructures.

- Collaborate with cross-functional teams to integrate ML solutions into research projects and mental health tools.

- Develop and maintain data pipelines for training, evaluating, and deploying models.

- Leverage expertise to create innovative solutions to complex problems using state-of-the-art ML methods.

- Ensure data quality, security, and compliance with privacy regulations.

- Perform additional job-related duties as assigned.

Qualifications:

- Master's degree in Neuroscience, Psychology, Engineering, Computer Science or equivalent combination of education and experience.

- 8+ years of experience in data analysis and data science fundamentals (e.g., algorithms, data structures, data visualization, machine learning).

- 8+ years of experience in at least one scientific programming language (e.g., Python/R, Matlab) and related toolboxes or frameworks (e.g., Tidyverse, Scipy, Sklearn, Polars, Pytorch) is required.

- 5+ years of experience working in a Linux environment, using version control systems (e.g., GitHub), and software virtualization platforms (e.g., Docker).

- 3+ years of practical experience developing and designing production-oriented machine learning technologies and systems, including hands-on experience in NLP and modern ML/NLP.toolchains (e.g., pytorch, tensorflow, SpaCy, HuggingFace, NLTK).

- Experience can be concurrent with education.

- Work cooperatively and contribute to group efforts in a very collaborative, open-source, and multidisciplinary environment.

- Good knowledge of standard office software applications (e.g., Microsoft Word, Excel, PowerPoint, etc.).

- Demonstrated track record of strong technical writing and communication skills.

- Understanding data privacy regulations (HIPAA, GDPR) and research ethics.

- Strong interpersonal skills, as well as strong written and oral communication.

- Ability to independently and responsibly contribute to data analysis and machine learning technologies in clinical contexts.

- Capable of mentoring staff tasked with machine learning model development.

- Identify and address challenges with innovative solutions.

- Skilled in planning, executing, and monitoring projects.

Special Considerations:

The anticipated salary range for this position is $118,000 - $148,000 USD annually.

Our client's competitive compensation and benefits include medical insurance, 401(k), paid parental leave, dependent care, flexible work schedules, discounted tickets and entertainment perks programs.

The salary range for the position is posted. Factors such as candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations affect the salary offered within this range. In addition, this salary may be subject to a geographic adjustment (according to a specific city and state and depending on the role), if an authorization is granted to work outside of the location listed in this posting.

Our client is an equal opportunity employer and does not discriminate in employment based on race, religion (including religious dress and grooming practices), color, sex/gender (including pregnancy, childbirth, breastfeeding or related medical conditions), sex stereotype, gender identity/gender expression/transgender (including whether or not you are transitioning or have transitioned) and sexual orientation; national origin (including language use restrictions and possession of a driver's license issued to persons unable to prove their presence in the United States is authorized under federal law [Vehicle Code section 12801.9]); ancestry, physical or mental disability, medical condition, genetic information/characteristics, marital status/registered domestic partner status, age (40 and over), sexual orientation, military or veteran status, or any other basis protected by federal, state or local law or ordinance or regulation.