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Machine Learning Defense Jobs in California (NOW HIRING)

VSolvit

DATA SCIENTIST II (MACHINE LEARNING)

Norco, CA · On-site

$115K - $130K/yr

Data Scientist II (Machine Learning) On Site: Norco, CA Job Summary We are seeking a talented and ... Experience working with classified government data or in a defense-related environment

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 ...

LLNL

Machine Learning Software Developer

Livermore, CA · On-site

... defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture ... We have an opening for a Machine Learning Software Developer to help to shape research and ...

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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 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 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 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
Principal Machine Learning Engineer, Alt Defense

Principal Machine Learning Engineer, Alt Defense

Roblox

San Mateo, CA • On-site

Full-time

Posted 3 days ago

Job description

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences- all created by our global community of developers and creators.
At Roblox, we're building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device.We're on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.
A career at Roblox means you'll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.
WHY SAFETY?
At Roblox, we strive to connect a billion people with optimism and civility, and the Safety organization's mission is to become the leader in civil immersive online communities. We systematically detect, remove, and prevent problematic accounts, content and behavior, and we make Roblox accounts secure and free from compromise. We cover a broad area of the tech spectrum, including machine learning, classifiers for 3D models, experimentation, automation, detection workflows, and AI-powered text filters. Aligned and partnering with product teams, we use this toolbelt to discover new opportunities, influence and shape the product roadmap and prioritization, build safety products, and measure the impact on our community of users and developers. In doing so, we keep Roblox safe, civil, and inclusive, and we foster positive relationships between people around the world.
WHY ALT DEFENSE?
Safety and Civility is Roblox's #1 priority. The Alt Defense pod is at the front lines of this mission, tasked with solving one of the most difficult adversarial problems on the platform: Alternate Account Detection and Prevention. When bad actors are removed from Roblox, they often attempt to return immediately with new identities. Our goal is to stop them in their tracks. As the Technical Lead for this pod, you will architect and build an industry-leading detection system that operates at a massive scale-processing billions of accounts and identifying recidivism within minutes. You will also be supporting additional use cases for alt detection across the company. You will report to the Senior Engineering Manager of the Account Identity Team.
You will:
  • Lead the technical vision for alternate account detection platform, moving from reactive measures to proactive, near real-time prevention.
  • Architect high-scale ML systems using Graph Neural Networks (GNNs) and advanced clustering techniques to map relationships across billions of entities.
  • Solve complex ground truth and training data challenges for adversarial usecases
  • Build for latency and scale, ensuring that detection happens within minutes of a bad actor's attempt to rejoin the platform.
  • Develop innovative adversarial approaches to stay ahead of sophisticated actors who use evolving techniques to mask their identity.
  • Drive the ML roadmap, identifying opportunities to leverage big data and behavioral signals to improve precision and recall in a high-stakes environment.
  • Mentor and up-level a pod of high-performing ML and software engineers, fostering a culture of technical excellence and rapid iteration.

You have:
  • MS or PhD degree in Computer Science, Machine Learning, or a related field.
  • 10+ years of industry experience in Applied ML, with a significant focus on anti-abuse, fraud, integrity, or identity.
  • Expertise in Graph Learning: Deep experience with Large-scale GNNs (GraphSAGE, PGB, etc.) and unsupervised/semi-supervised clustering at the scale of billions of nodes.
  • Proven track record of leading complex technical projects from conception to production-level deployment.
  • Experience with high-throughput systems: You understand the nuances of deploying ML models in low-latency environments where "time-to-detect" is a critical KPI.
  • Adversarial mindset: You can think like a bad actor to anticipate how they will circumvent detection and build robust defenses against it.

You are:
  • Resourceful: You're adaptable in any situation and can always find a path forward in the face of evolving threats.
  • Analytical: Excited to investigate large, ambiguous datasets to find the "signal in the noise" of billions of accounts.
  • User Oriented: You understand that safety measures must be balanced with a seamless experience for our legitimate community members.
  • Team Oriented: You are a sought-after mentor who lifts up your peers and builds a collaborative, high-performance environment.
  • Mission Oriented: You are laser-focused on keeping Roblox safe and are willing to take bold, strategic risks to achieve a billion-user scale safely.

For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.
Annual Salary Range
$295,250-$345,040 USD
Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).
Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.
For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.

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