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Remote Cyber Security Machine Learning Jobs (NOW HIRING)

Syngenta

Machine Learning Engineer

NC · Remote

This is an opportunity to apply cutting-edge remote sensing and AI technologies to solve real-world ... Contribute across the full lifecycle of machine learning projects, including problem definition ...

CrowdStrike

Sr. Machine Learning Engineer (Remote)

$107K - $146K/yr

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies ... CrowdStrike is looking for a Sr. Machine Learning Engineer to join our growing AIDR Engineering ...

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

... Machine Learning, Cyber Security and Cutting Edge Technology across the US Government. Be a part of something special! Role and Responsibilities Model Development * Collaborate with data scientists ...

Apex Informatics

Machine Learning Engineer

Remote We are seeking an Applied Machine Learning Engineer with a strong focus on practical solutions and software development (ability to work on both open-ended research problems and production ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

Weekday AI

Machine Learning & NLP Expert

$80 - $110/hr

This is a part-time, fully remote opportunity requiring approximately 20 hours per week . Requirements Key Responsibilities * Design challenging, real-world machine learning and natural language ...

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Remote Cyber Security Machine Learning information

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$40.5K

$122.9K

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

As of Sep 11, 2026, the average yearly pay for remote cyber security machine learning in the United States is $122,890.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,000.00 and $142,000.00 per year, depending on experience, location, and employer.

What is a remote cyber security machine learning specialist?

A Remote Cyber Security Machine Learning job involves using machine learning techniques to detect, prevent, and respond to cyber threats, all while working from a remote location. Professionals in this role develop and deploy algorithms that can identify patterns of malicious activity, automate threat detection, and enhance security protocols. They work with large datasets, collaborate with security teams, and continuously update models to address emerging threats. This position combines expertise in both cyber security and machine learning, making it critical for modern, data-driven security operations.

What are the key skills and qualifications needed to thrive as a remote cyber security machine learning specialist?

To excel in a Remote Cyber Security Machine Learning role, you need a strong background in computer science, cybersecurity principles, and machine learning algorithms, typically supported by a relevant degree and experience. Familiarity with tools like Python, TensorFlow, PyTorch, and security platforms such as SIEM systems, along with certifications like CISSP or CEH, is often required. Excellent analytical thinking, problem-solving skills, and clear remote communication set top performers apart. These abilities are crucial for proactively identifying and mitigating threats using advanced AI techniques while collaborating effectively in distributed teams.

How does a remote cyber security machine learning specialist typically collaborate with cross-functional teams?

As a Remote Cyber Security Machine Learning professional, you'll often work closely with cybersecurity analysts, data engineers, and IT staff to design, implement, and refine machine learning models that detect and prevent threats. Collaboration happens primarily through virtual meetings, shared documentation, and project management tools, ensuring that everyone stays aligned despite geographic distances. Clear communication and proactivity are key, as you'll need to translate complex machine learning concepts into actionable insights for team members with varying technical backgrounds. Regular updates and feedback loops help ensure that models are robust, effective, and aligned with organizational security goals.

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

AspectRemote Cyber Security Machine LearningRemote Cyber Security Analyst
Required CredentialsCertifications in cybersecurity and machine learning (e.g., CISSP, CompTIA Security+, Python, ML certifications)Certifications in cybersecurity (e.g., CISSP, CompTIA Security+)
Work EnvironmentFocus on developing algorithms, analyzing data, and automating security processesMonitoring security alerts, investigating incidents, and implementing security measures
Employer & Industry UsageTech companies, cybersecurity firms, organizations leveraging AI for securityOrganizations across industries needing security monitoring and incident response

Remote Cyber Security Machine Learning specialists develop AI-driven security tools, while Remote Cyber Security Analysts focus on monitoring and responding to threats. Both roles require cybersecurity knowledge, but the former emphasizes data analysis and machine learning skills, whereas the latter concentrates on security operations and incident management.

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Remote Cyber Security Machine Learning jobs near you
Infographic showing various Remote Cyber Security Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $122,890 per year, or $59.1 per hour.

Machine Learning Engineer

San Francisco, CA • On-site, Remote

Swish Analytics
Spectator Sports • 1 - 10 employees
Learn more about Swish Analyticsexternal

$160K/yr

Full-time

Re-posted 25 days ago

Job description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and enterprise clients.
The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to "roll your own" and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.
This position is 100% remote
Responsibilities:
  • Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency.
  • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow.
  • Build, test, deploy and maintain production systems.
  • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages.
  • Support maintenance and optimization of cloud-native EDW and ETL solutions.
  • Maintain and promote best practices for software development, including deployment process, documentation, and coding standards.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Use extensive experience to build, test, debug, and deploy production-grade components.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Participate in development of database structures that fit into the overall architecture of Swish systems

Qualifications:
  • Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area
  • 5+ years of demonstrated experience developing and delivering clean and efficient production code to serve business needs
  • A proven background in quantitative analytics, trading, or engineering is required for this position
  • Demonstrated experience developing data science modeling systems and infrastructure at scale
  • Experience with Python and exposure to modern machine learning frameworks
  • Proficient in SQL; experience with MySQL
  • Background and/or interest in Rust preferred
  • Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback
  • Strong communication skills when discussing technical concepts with technical and non-technical colleagues

Base salary: starting at $160,000 base plus bonus potential
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Engineering & Infrastructure Role Data Science Infrastructure Locations San Francisco, CA - Remote Remote status Fully Remote

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