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Manager Cyber Security Machine Learning Jobs (NOW HIRING)

BayCare Health System

Manager Cybersecurity

Clearwater, FL · On-site

$102.30K - $138.30K/yr

The Manager Cybersecurity: * Responsible for the operational oversight and execution of information ... Develops team members and teams by empowering them, setting clear expectations, providing learning ...

Extend

Manager, Machine Learning

$180K - $210K/yr

Required: * 6+ years of work experience building and deploying machine learning systems into production * 2+ years experience mentoring and managing ML teams * Strong proficiency in Python and SQL

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Manage machine learning algorithm lifecycle. * Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Manage machine learning algorithm lifecycle. * Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$112.10K - $154K/yr

Apply cybersecurity principles in the design and deployment of machine learning systems. * Provide documentation, technical reports, and engineering artifacts consistent with PMAT and government ...

Peet's Coffee

Senior Manager, Cyber Security

Emeryville, CA · Hybrid

$160K - $180K/yr

Peet's is seeking a Senior Manager, Cyber Security to lead and mature the company's enterprise ... Provide coaching and learning opportunities to teams ensuring leading edge practices * Influential ...

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How much do manager cyber security machine learning jobs pay per year?

As of May 31, 2026, the average yearly pay for manager cyber security machine learning in the United States is $132,962.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $150,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Manager Cyber Security Machine Learning, and why are they important?

To thrive as a Manager Cyber Security Machine Learning, you need deep expertise in cybersecurity principles, machine learning algorithms, and a relevant degree such as computer science or information security. Familiarity with security tools (e.g., SIEM, IDS/IPS), machine learning frameworks (like TensorFlow or PyTorch), and certifications such as CISSP or CEH is highly valuable. Exceptional leadership, problem-solving, and communication skills help in managing cross-functional teams and translating complex technical concepts to stakeholders. These skills are crucial for protecting organizational assets through advanced analytics and leading teams that can adapt to emerging cyber threats.

What are the unique challenges a Manager of Cyber Security Machine Learning faces when integrating AI-driven solutions into existing security frameworks?

One of the main challenges for a Manager of Cyber Security Machine Learning is ensuring that machine learning models are robust against adversarial attacks and do not introduce new vulnerabilities. Integrating AI-driven solutions also requires close collaboration with both cybersecurity and data science teams to align security goals and technical constraints. Additionally, managers must oversee continuous monitoring, model updating, and compliance with privacy regulations to maintain the effectiveness and trustworthiness of these systems. Balancing innovation with risk management is a key part of this role.

What does a Manager of Cyber Security Machine Learning do?

A Manager of Cyber Security Machine Learning leads teams that develop and implement machine learning models to detect and prevent cyber threats. They oversee projects that use AI to analyze large datasets for signs of malicious activity, automate threat response, and improve security operations. This role requires both technical expertise in cybersecurity and machine learning, as well as leadership skills to manage teams and collaborate with other departments. Their goal is to enhance an organization’s security posture by leveraging cutting-edge technologies.

What is the difference between Manager Cyber Security Machine Learning vs Security Analyst?

AspectManager Cyber Security Machine LearningSecurity Analyst
Required CertificationsCertified Information Systems Security Professional (CISSP), Certified Ethical Hacker (CEH), or specialized machine learning certificationsCompTIA Security+, GIAC Security Essentials (GSEC), or CISSP
Work EnvironmentLeads teams, develops ML-based security solutions, collaborates with data scientists and engineersMonitors security systems, investigates incidents, implements security measures
Employer & Industry UsageTech companies, financial institutions, cybersecurity firms integrating ML for threat detectionOrganizations across industries focusing on threat analysis and security monitoring

The Manager Cyber Security Machine Learning focuses on leading teams and developing ML-driven security strategies, while the Security Analyst primarily monitors and responds to security threats. Both roles require security certifications, but the manager role emphasizes leadership and ML expertise, whereas the analyst role centers on operational security tasks.

More about Manager Cyber Security Machine Learning jobs
What are the most commonly searched types of Cyber Security Machine Learning jobs? The most popular types of Cyber Security Machine Learning jobs are:
What job categories do people searching Manager Cyber Security Machine Learning jobs look for? The top searched job categories for Manager Cyber Security Machine Learning jobs are:
Manager Cyber Security Machine Learning jobs near you
Infographic showing various Manager Cyber Security Machine Learning job openings in the United States as of May 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 66% Physical, 6% Hybrid, and 28% Remote job distribution, with an average salary of $132,962 per year, or $63.9 per hour.
Machine Learning Engineer

Machine Learning Engineer

UnifyID (acquired by Prove)

Redwood City, CA

Full-time

Posted 22 days ago

Job description

About Prove (acquired UnifyID)
Prove is the modern platform for continuous identity authentication and is used by over 1,000 enterprises and 500 financial institutions, including 9 of the top 10 U.S. banks. Prove’s cloud solutions, and mobile intelligence-driven APIs can be easily orchestrated to increase Approve Rates to over 90%, enabling companies to authenticate customer identities accurately, effortlessly, and privately while mitigating fraud. Prove’s solutions are available in 195 countries.

For the latest updates from Prove, follow us on LinkedIn.

About the role
We are looking for a seasoned software engineer to join our A+ technical team in designing, building and deploying machine learning solutions into production.

UnifyID is building a platform to solve one the world’s biggest unsolved security problems in a completely novel way, requiring us to push the boundaries of what’s possible in production machine learning and on mobile devices.  Our data analytics platform can translate mobile sensor data from real-world human activity into a “digital fingerprint” with no conscious action from the user, all in real-time, and in a way that respects user privacy.  This is an opportunity to be a part of something truly unique and game-changing.

We are looking for natural-born builders who are comfortable in multiple technical areas, have creative problem-solving skills, a love for coding and technology and a “get stuff done” attitude.
Your day-to-day
  • Be an early member of a high-performing team of software engineers and machine learning researchers building a new human identity platform
  • Take ownership, be creative, and think outside the box to invent and build solutions to real-world customer problems
  • Interface with our world-class machine learning research team to help turn core research into reality
  • Wrangle and perform experiments on petabyte-scale data sets
  • Wear many hats to make things happen in a dynamic startup environment
  • Bring your own unique expertise to the team and learn from others
  • Enjoy tight collaboration with your teammates
Ideal candidates will have...
  • Spent at least 5 years in the trenches of the software industry, delivering quality software that matters to people that care
  • Many “been there, done that” stories related to shipping and maintaining major software products for customers
  • Excellent coding skills in an object-oriented language (Go, Python, Rust, Java, C++, Ruby, etc...)
  • Experience working with high volumes of data, ideally with machine learning playing a critical role
  • Strong foundational knowledge of mathematics, bonus if related to machine learning or signals processing
  • A breadth of technical skills and know how to use the right tool for the job
  • High motivation and ability to learn new technologies and domains 
  • A positive can-do attitude and bring a passion for excellence to the workplace
  • Excellent collaboration and communication skills
  • Professional experience with AWS, Kubernetes a bonus
  • Knowledge of cybersecurity, signals processing, or experience working with time-series data a bonus
Join us!
As we continue to scale our company, we are looking for people who know how to make an impact. We’re talking self-starting professionals who thrive in a fast-paced environment, process information quickly, and make intelligent decisions. The work is challenging and requires not only smarts but natural curiosity and tenacity. Teamwork is also important to us – we work together and play together.

Prove has big plans; we’re excited and optimistic about the future. If this sounds like a career for you – come check us out.

This team is located in the heart of Silicon Valley in downtown Redwood City and has unparalleled access to deep entrepreneurial expertise, high-caliber academic research institutions, and top-tier VC resources.

Finally, it is important that you be authentic and be yourself.

Prove is an equal opportunity employer committed to providing equal employment opportunity for all people regardless of race, color, religion, gender or sexual orientation, age, marital status, national origin, citizenship status, disability, veteran status, or other personal characteristics.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.