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Privacy Preserving Machine Learning Jobs in New York

New York University

Research Engineer

New York, NY · On-site

$34.34/hr

Responsible for researching new techniques for privacy-preserving machine learning. * Expected to contribute to advances in fully homomorphic encryption compiler infrastructure * Expected to ...

MasterCard

Senior Data Scientist

New York, NY

... privacy-preserving techniques, and digital advertising measurement. All About You Experience in Data Science, Machine Learning, AdTech (Preferred), Marketing Science, or a related field is required ...

TekShapers

Senior Data Scientist

Raritan, NJ · On-site

... machine learning models and deploying them in a cloud environment, preferably on Google Cloud ... Knowledge of privacy-preserving ML methods (differential privacy, synthetic data) and data lineage ...

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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 are popular job titles related to Privacy Preserving Machine Learning jobs in New York? For Privacy Preserving Machine Learning jobs in New York, the most frequently searched job titles are:
What job categories do people searching Privacy Preserving Machine Learning jobs in New York look for? The top searched job categories for Privacy Preserving Machine Learning jobs in New York are:
What cities in New York are hiring for Privacy Preserving Machine Learning jobs? Cities in New York 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 New York as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Research Engineer

New York University

New York, NY • On-site

$34.34/hr

Full-time, Part-time

Re-posted 21 days ago

New York University rating

8.5

Company rating: 8.5 out of 10

Based on 46 frontline employees who took The Breakroom Quiz

80th of 618 rated colleges and universities

Job description

Description
PART TIME RESEARCH ENGINEER
Center for Cyber Security
New York University Tandon School of Engineering
The NYU Center for Cybersecurity (CCS) represents an interdisciplinary collaboration between the NYU School of Law, the Tandon School of Engineering, the Steinhardt School of Culture, Education, and Human Development, and various other university departments. Maintaining a physical presence in both New York City and Abu Dhabi, the Center operates alongside a global network of scholars and practitioners spanning Europe, Asia, the Middle East, and North America. The research and educational programs led by CCS are defining the frontiers of cybersecurity, cultivating resilience against emerging threats to security, safety, privacy, software, and hardware integrity, alongside the infrastructure of global modern life. Furthermore, CCS educational initiatives, spanning certificate and online degree programs, facilitate the efficient adoption of important new technologies across various organizations. These initiatives have also received formal recognition in Cyber Defense, Cyber Operations, and Cyber Research from the National Centers of Academic Excellence in Cybersecurity. NYU CCS is seeking to hire a part-time research scientist to assist with these ongoing activities.
New York University (NYU) is one of the top private universities in the United States. The Tandon School of Engineering, located in Brooklyn, NY, is deeply committed to excellence in teaching and learning. Tandon fosters innovation and entrepreneurship among students and faculty, making a difference in the world.
RESPONSIBILITIES
The successful candidate will be:
  • Expected to process documentation and contribute to scientific writing for projects related to nanofabrication.
  • Responsible for researching new techniques for privacy-preserving machine learning.
  • Expected to contribute to advances in fully homomorphic encryption compiler infrastructure
  • Expected to contribute to new methods for developing neural network architectures that are more amenable to AI.

SALARY RANGE
In accordance with the NYC Pay Transparency Act, the part time base salary for this role is $34.34 per hour, commensurate with the candidate's professional experience and qualifications.
EXPECTED START DATE AND PERIOD OF EMPLOYMENT
The anticipated start date is July 1, 2026. This appointment is for a duration of up to 3 months, contingent upon the availability of funds. The part-time schedule requires a commitment of approximately 25 hours per week.
Qualifications
Candidates are expected to hold at least a PhD in Engineering, Electrical Engineering or a related discipline for at least 3 years of hands-on computer engineering experience. Candidates will be required to provide proof of eligibility to work in the United States upon hire.
They should also have a proven track record in nanofabrication and scientific writing. A publication record demonstrating hands-on research experience is necessary
Application Instructions
Interested applicants should provide the following documentation:
• A cover letter
• A current CV, including a comprehensive list of publications
All materials must be submitted electronically through Interfolio and sent to: bjr5@nyu.edu
Review of applications will commence immediately and continue until the position is successfully filled.

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About New York University

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Since its founding in 1831, NYU has been an innovator in higher education, reaching out to an emerging middle class, embracing an urban identity and professional focus, and promoting a global vision that informs its 20 schools and colleges. Today, that trailblazing spirit makes NYU one of the most prominent and respected research universities in the world, featuring top-ranked academic programs and accepting fewer than one in eight undergraduates. Anchored in New York City and with degree-granting campuses in Abu Dhabi and Shanghai as well as 12 study away sites throughout the world, NYU is a leader in global education, with more international students and more students studying abroad than any other US university.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1831

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