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Privacy Preserving Machine Learning Jobs in Cambridge, MA

Accenture

Senior Data Scientist

Boston, MA · On-site

Develop supervised and unsupervised machine learning solutions, including classification ... Experience with AI governance, Responsible AI, model risk, data ethics, privacy, security ...

New

Chewy

Data Scientist I

Boston, MA · On-site

$117K - $163K/yr

Develop machine learning applications according to requirements; design, code, test, deploy and ... To access Chewy's California CPRA Job Applicant Privacy Policy, please click here.

Meta

Research Scientist Intern, AI Alignment

Boston, MA

$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 ...

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 ...

Azenta

Senior Product Data Analyst

Burlington, MA

Identify opportunities to apply Artificial Intelligence (AI), Machine Learning (ML), automation ... Promote responsible AI practices, including explainability, human oversight, data privacy, security ...

Azenta

Senior Product Data Analyst

Burlington, MA · On-site

Identify opportunities to apply Artificial Intelligence (AI), Machine Learning (ML), automation ... Promote responsible AI practices, including explainability, human oversight, data privacy, security ...

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Showing results 41-60

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 Aug 12, 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 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 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 1% As Needed, 69% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $126,244 per year, or $60.7 per hour.

Machine Learning Scientist I/II, Multi-Modal Scientific Reasonings

Lila Sciences

Cambridge, MA • On-site

$176K - $304K/yr

Full-time

Medical, Dental, Vision, Life

Re-posted 9 days ago

Job description

Your Impact at LILA
We're hiring a Machine Learning Scientist to advance multi-modal reasoning with vision-language models (VLMs) on real-world scientific data including, but not limited to: figures and plots, microscopy data from diverse sources. You'll design and build state-of-the-art methods to advance the state of Scientific Superintelligence.
What You'll Be Building
  • Lead research on multi-modal reasoning systems that interpret scientific data (images, plots, text, etc) using state-of-the-art and custom VLMs.
  • Design training, adaptation and test-time methods and strategies (e.g., instruction tuning, supervised learning, RLHF, RAG) for scientific understanding tasks.
  • Build datasets and benchmarks from real scientific artifacts (e.g., microscopy, spectra, protocols) to understand model performance.
  • Develop perception modules (e.g, OCR, table/structure recognition, plot parsing) for multi-modal data modalities.
  • Collaborate with domain scientists and engineers to scale research into production ready systems for scientific superintelligence.

What You'll Need to Succeed
  • Advanced degree in a relevant field (CS/AI, Applied Math/Stats, EE) or a physical-sciences discipline (Materials, Chemistry, Physics) with strong ML focus; or equivalent research/industry experience.
  • Track record in multi-modal ML or VLMs demonstrated via shipped systems, publications, or open-source.
  • Understanding of scientific QA/benchmarks and custom evaluation design.
  • Experience with multi-modal fine-tuning, document parsing & understanding, dataset curation and benchmarking.
  • Strong engineering skills centered on modern machine learning frameworks (e.g., PyTorch, Huggingface).
  • Clear communication and collaboration in cross-functional settings.

Bonus Points For
  • Experience with scientific data modalities in real-world laboratories such as microscopy images.
  • Publications in top ML/CV/NLP venues or tangible impact in applied industrial research.
  • Contributions to open-source multi-modal tooling, evaluation suites, or datasets.

Compensation
We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.
International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range
$176,000-$304,000 USD
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.
Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
We're All In
Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

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