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Privacy Preserving Machine Learning Jobs in Cambridge, MA

Axon

Privacy & AI Counsel

Boston, MA · On-site

$135K - $190K/yr

From body-worn cameras and SaaS platforms to machine learning models and global privacy frameworks, you'll play a critical role in answering complex questions in highly regulated markets around the ...

Mass General Brigham

Research Fellow (Miller)

Boston, MA · On-site

$70K - $71K/yr

Complete Machine Learning analyses, data analysis and data presentation * Take administrative ... HIPAA Privacy Training and Sanctions All employees who have access to health information whose ...

Massgeneralbrigham

Research Fellow (Miller)

Boston, MA

$70K - $71K/yr

Complete Machine Learning analyses, data analysis and data presentation * Take administrative ... HIPAA Privacy Training and Sanctions All employees who have access to health information whose ...

Meta

Research Scientist Intern, AI Alignment

Boston, MA · On-site

$7.6K - $12K/mo

... machine learning, reinforcement learning, computational statistics, applied mathematics and security/privacy. Our interns have an opportunity to make core algorithmic advances and apply their ideas ...

UKG, Inc.

Sr Director Data Science

Lowell, MA · On-site

AI & Machine Learning Delivery Lead development of predictive, prescriptive, and generative AI ... Champion responsible AI practices including fairness, explainability, privacy, security, and ...

UKG

Sr Director Data Science

Lowell, MA

AI & Machine Learning Delivery Lead development of predictive, prescriptive, and generative AI ... Champion responsible AI practices including fairness, explainability, privacy, security, and ...

OneStudyTeam

Senior Data Scientist

Boston, MA · On-site +1

$140K - $190K/yr

... machine learning algorithms to improve patient enrollment and trial management. You'll work in a highly regulated healthcare data environment, ensuring compliance with privacy standards while ...

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All JobsPrivacy Preserving Machine Learning JobsPrivacy Preserving Machine Learning Jobs in Cambridge, MA

Privacy Preserving Machine Learning information

See Cambridge, MA salary details

$108.8K

$126.2K

$141.5K

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

As of Sep 2, 2026, the average yearly pay for privacy preserving machine learning in Cambridge, MA is $126,244.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,400.00 and $141,000.00 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 are popular job titles related to Privacy Preserving Machine Learning jobs in Cambridge, MA?

For Privacy Preserving Machine Learning jobs in Cambridge, MA, the most frequently searched job titles are:

What job categories do people searching Privacy Preserving Machine Learning jobs in Cambridge, MA look for?

The top searched job categories for Privacy Preserving Machine Learning jobs in Cambridge, MA are:

What cities near Cambridge, MA are hiring for Privacy Preserving Machine Learning jobs?

Cities near Cambridge, MA 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 Cambridge, MA as of August 2026, with employment types broken down into 85% Full Time, and 15% Contract. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $126,244 per year, or $60.7 per hour.

Senior Machine Learning Engineer, AI Platform

Whoop

Boston, MA • On-site

$133K - $175K/yr

Full-time

Re-posted yesterday

Job description

At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level and live longer by using AI to transform continuous physiological data into clear insights and actionable recommendations. Our AI platform is central to this mission, turning raw physiological signals into trusted, personalized guidance that members can act on every day.
WHOOP is hiring a Senior AI/ML Engineer to help scale the intelligence layer behind WHOOP's AI-powered experiences, including WHOOP Coach, AI-powered Support, and new intelligent features across the product. In this role, you will own core components of the AI Platform that power our internal AI Studio: evaluation pipelines, fine-tuning workflows, LLM observability, and experimentation tooling. You will partner closely with product and data science to translate real member needs into reliable, impactful AI systems that improve continuously based on real-world usage.
RESPONSIBILITIES:
  • Design, build, and operate production AI systems and scaffolding around language models that power conversational, predictive, and generative capabilities across WHOOP products.
  • Lead end-to-end AI system initiatives spanning problem definition, data flows, dataset design, evaluation harnesses, deployment, and iteration in close partnership with data science and product.
  • Build and maintain pipelines for collecting, curating, and reshaping messy, multi-source data into high-quality, well-structured training and evaluation datasets for language model-based systems.
  • Operationalize fine-tuning and evaluation workflows for large language models behind member-facing features such as WHOOP Coach and AI Support, including defining datasets, labels, and taxonomies that reflect real member needs.
  • Develop tooling and frameworks that make experimentation, offline/online evaluation, and model deployment faster, safer, and more repeatable, including robust observability for AI features in production.
  • Build and maintain feedback loops that connect real member interactions, offline evaluations, and training data updates so that models improve continuously based on real-world behavior.
  • Mentor other engineers and data scientists, share best practices in applied AI/ML, and help elevate the overall technical bar of the AI Platform team.

QUALIFICATIONS:
  • 3+ years of experience in applied machine learning, AI engineering, or ML-focused software engineering roles, including significant work in production environments.
  • Hands-on experience building with modern language models (open-weight or API-based), including prompt design, fine-tuning, and rigorous evaluation.
  • Solid working understanding of ML fundamentals (dataset construction, feature engineering, training workflows, evaluation metrics, experiment design) sufficient to make good engineering tradeoffs and partner effectively with data scientists.
  • Familiarity with modern LLM training and alignment techniques such as supervised fine-tuning (SFT), direct preference optimization (DPO), and reinforcement learning (RL), and how they influence data requirements, evaluation strategies, and system design in production.
  • Proven track record building, shipping, and operating ML-powered systems end to end, from data pipelines (batch and/or streaming) that transform large datasets into usable training and evaluation sets to production deployments with inference optimization, observability, and lifecycle management.
  • Strong proficiency in data manipulation and analysis, including working with messy, multi-source, and semi-structured data and translating product questions into well-defined datasets, labels, and evaluation splits.
  • Familiarity with best practices for secure, privacy-aware AI and working with sensitive data.
  • Excellent communication and collaboration skills, with the ability to influence across teams and drive alignment on technical direction.

Learn more about our Software Org and how to be successful in your engineering career at WHOOP via our Career Framework. Also check out our AI studio blog here.
This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
Interested in the role, but don't meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.
At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company's long-term growth and success.
The U.S. base salary range for this full-time position is$150,000 - $210,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.
In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.
These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate's specific qualifications, expertise, and alignment with the role's requirements.
Learn more about WHOOP.
Whoop logo

About Whoop

Sourced by ZipRecruiter

At WHOOP, we're on a mission to unlock human performance. WHOOP empowers users (Olympians, Professional Athletes, Fitness Enthusiasts, etc) to perform at a higher level through a deeper understanding of their bodies and daily lives.

Industry

Fitness and sports centers

Company size

501 - 1,000 Employees

Headquarters location

Boston, MA, US

Year founded

2012

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