Machine Learning Engineer (PhD or MS Required) 756
Protegrity USA Inc
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 missioncritical, 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 handson building secure AI workflows and agentic systems in a highly collaborative, hybrid/inoffice 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.
- 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
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