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Machine Learning Defense Jobs in California (NOW HIRING)

Voltai, Inc

Machine Learning Engineer

Palo Alto, CA · On-site

... of Defense, National Security Advisor, and Senior Foreign-Policy Advisor to four US presidents. What we're Looking For * Strong AI/ML engineering skills from top tier CS, EECS, Math and Physics ...

Voltai

Machine Learning Engineer

Palo Alto, CA · On-site

... of Defense, National Security Advisor, and Senior Foreign-Policy Advisor to four US presidents. What we're Looking For * Strong AI/ML engineering skills from top tier CS, EECS, Math and Physics ...

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Machine Learning Defense information

What are the key skills and qualifications needed to thrive as a Machine Learning Defense professional, and why are they important?

To thrive as a Machine Learning Defense professional, you need a strong background in computer science, cybersecurity, and machine learning, often supported by degrees in these fields or related certifications. Familiarity with frameworks like TensorFlow or PyTorch, experience with adversarial machine learning techniques, and knowledge of security protocols are typically required. Critical thinking, problem-solving, and strong communication skills are essential for anticipating threats and collaborating with interdisciplinary teams. These skills ensure that AI systems remain robust and secure against evolving cyber threats, protecting sensitive data and organizational integrity.

What is machine learning defense?

Machine learning defense refers to techniques and strategies designed to protect machine learning models from various security threats, such as adversarial attacks, data poisoning, and model theft. These defenses can include methods like adversarial training, input sanitization, and robust model architectures. The goal is to ensure that machine learning systems remain accurate, reliable, and safe even when faced with malicious attempts to manipulate or exploit them. As machine learning becomes more widely adopted, the importance of effective defenses continues to grow.

What are some common challenges faced by professionals in Machine Learning Defense roles, and how can they be addressed?

Professionals in Machine Learning Defense often encounter challenges such as staying ahead of adversarial attacks, managing model robustness, and keeping up with rapidly evolving threat landscapes. Addressing these challenges typically requires continuous learning, collaboration with cybersecurity and data science teams, and implementing rigorous testing and monitoring frameworks for deployed models. Proactively participating in industry forums and staying updated on the latest research also help in identifying emerging threats and mitigation strategies.
What are popular job titles related to Machine Learning Defense jobs in California? For Machine Learning Defense jobs in California, the most frequently searched job titles are:
What job categories do people searching Machine Learning Defense jobs in California look for? The top searched job categories for Machine Learning Defense jobs in California are:
What cities in California are hiring for Machine Learning Defense jobs? Cities in California with the most Machine Learning Defense job openings:
Machine Learning Defense jobs near you
Infographic showing various Machine Learning Defense job openings in California as of July 2026, with employment types broken down into 91% Full Time, 5% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.

Machine Learning Engineer

Voltai, Inc

Palo Alto, CA • On-site

Full-time

Posted 24 days ago

Job description

About Voltai
Voltai is developing world models, and agents to learn, evaluate, plan, experiment, and interact with the physical world. We are starting out with understanding and building hardware; electronics systems and semiconductors where AI can design and create beyond human cognitive limits.
About the Team
Backed by Silicon Valley's top investors, Stanford University, and CEOs/Presidents of Google, AMD, Broadcom, Marvell, etc. We are a team of previous Stanford professors, SAIL researchers, Olympiad medalists (IPhO, IOI, etc.), CTOs of Synopsys & GlobalFoundries, Head of Sales & CRO of Cadence, former US Secretary of Defense, National Security Advisor, and Senior Foreign-Policy Advisor to four US presidents.
What we're Looking For
  • Strong AI/ML engineering skills from top tier CS, EECS, Math and Physics programs.
  • Proven track record of delivering AI/ML projects from concept to production.
  • Hands-on experience fine-tuning and deploying large language models (LLMs) in production environments.
  • Prior experience working with multi-modal models (e.g., combining text, image, or audio inputs).

Bonus Points
  • Background in competitive programming.
  • Contributions to open-source initiatives.
  • Notable awards or publications in leading journals/conferences.
  • Experience thriving in a fast-paced, hyper-growth startup environment.

Apply