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Machine Learning Engineer (PhD or MS Required) 756

Protegrity -
Palo Alto, CA

Apply Now

Job Details

Full-time
$189,100 - $211,800 a year

Qualifications

AI models
TensorFlow
PyTorch
Generative models
AI platforms (beyond public GPTs)
Machine intelligence
Machine learning libraries
Machine learning frameworks
Generative AI

Full Job Description

At Protegrity, we lead innovation by using AI and quantum-resistant cryptography to transform data protection across cloud-native, hybrid, on-premises, and open source environments. We leverage advanced cryptographic methods such as tokenization, format-preserving encryption, and quantum-resilient techniques to protect sensitive data. As a global leader in data security, our mission is to ensure that data isn’t just valuable but also usable, trusted, and safe.

Protegrity offers the opportunity to work at the intersection of innovation and collaboration, with the ability to make a meaningful impact on the industry while working alongside some of the brightest minds. Together, we are redefining how the world safeguards data, enabling organizations to thrive in a GenAI era where data is the ultimate currency. If you're ready to shape the future of data security, Protegrity is the place for you.

Protegrity is seeking a Machine Learning Engineer (PhD or Master’s degree required) to join our GenAI team at a pivotal moment in the market. As enterprises race to adopt Generative AI, securing AI workflows, data, and privacy has become mission‑critical, and Protegrity is at the forefront of making GenAI safe for real world, enterprise use.

This role is designed for a PhD or Master’s graduate with 2+ years of GenAI experience (or equivalent advanced research or technical projects), who wants to work hands‑on building secure AI workflows and agentic systems in a highly collaborative, hybrid/in‑office environment.

Responsibilities:

Develop and test GenAI architectures using agentic coding IDEs.
Conduct experiments and summarize findings.
Present research and experimental results to the team.
Fine-tune LLMs and embedding models.
Apply ML algorithms to large datasets.
Process structured and unstructured data.
Participate in architectural design and roadmap discussions.

Requirements:

PhD or Master's Degree required
2+ years of hands-on GenAI experience or equivalent projects.
2+ years of hands-on Python coding experience.
Experience with PyTorch, TensorFlow.
Solid understanding of ML algorithms and metrics.
Exposure to data security, data privacy, cybersecurity practices an asset.
Strong collaboration and learning mindset

Should you accept this position, you will be required to consent to and successfully complete a background investigation. This may include, subject to local laws, verification of extended education and additional criminal and civil checks.

We offer a competitive salary and comprehensive benefits with generous vacation and holiday time off. All employees are also provided access to ongoing learning & development.

Ensuring a diverse and inclusive workplace is our priority. We are committed to an environment of acceptance where you are free to bring your full self to work. All qualified applicants and current employees will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability or veteran status.

Please reference Section 12: Supplemental Notice for Job Applicants in our Privacy Policy to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Protegrity USA, Inc., or its parent company, subsidiaries or affiliates, and the purposes for which we use such personal information.

Apply Now

Refine Your Search

algorithm quantum algorithm hybrid generative ai jobs

Machine Learning Engineer (PhD or MS Required) 756

Software Engineer III, Quantum (multiple openings)

HPE Labs - Senior QEC Researcher – Integrated HPC & Quantum Solutions

Quantum Applications Architect

Senior Software Engineer

Quantum Software Engineer II

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