2

Remote Cyber Security Machine Learning Jobs (NOW HIRING)

Machine Learning Engineer

Burlington, MA ยท Remote

$165K - $200K/yr

S. government security clearance in the future.' This is NOT a fully remote position! Required * BS, MS, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Machine Learning, AI ...

Remote (United States) Employment Type: Direct Hire - Full-Time Compensation: $180K-$250K - based ... Cybersecurity * Healthcare Technology * Other high-stakes machine learning domains Education ...

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

Machine Learning Engineer

Washington, DC ยท On-site +1

$130K - $200K/yr

About the Role We are seeking a Machine Learning Engineer to design, build, and evaluate advanced ... Fully remote, U.S.-based * Health Benefits : Comprehensive health, dental, and vision coverage

Machine Learning Engineer

San Francisco, CA ยท On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

Machine Learning Engineer

Mountain View, CA ยท On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

Machine Learning Engineer - Remote

Vienna, VA ยท 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 ...

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 ...

Machine Learning Engineer

Bellevue, WA ยท On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

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 ...

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 ...

This is a remote opportunity for an experienced Machine Learning Specialist to design and deliver data-driven products and AI solutions. You will work across machine learning, data science, analytics ...

Machine Learning Engineer

San Diego, CA ยท On-site +1

$109K/yr

Own small to medium components of machine learning systems from technical designthrough ... Ability to work effectively in a remote environment using collaboration tools Preferred Experience ...

Own small to medium components of machine learning systems from technical designthrough ... Ability to work effectively in a remote environment using collaboration tools Preferred Experience ...

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 ...

Showing results 21-40

Remote Cyber Security Machine Learning information

See salary details

$40.5K

$122.9K

$180K

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

As of Aug 21, 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.

More about Remote Cyber Security Machine Learning jobs

What cities are hiring for Remote Cyber Security Machine Learning jobs?

Cities with the most Remote Cyber Security Machine Learning job openings:

What are the most commonly searched types of Cyber Security Machine Learning jobs?

The most popular types of Cyber Security Machine Learning jobs are:

Infographic showing various Remote Cyber Security Machine Learning job openings in the United States as of August 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $122,890 per year, or $59.1 per hour.

Machine Learning Engineer

MatrixSpace

Burlington, MA โ€ข Remote

$165K - $200K/yr

Full-time

Re-posted 14 days ago


Job description

Help us bridge machine learning research and real-world deployment!

MatrixSpace develops AI-enabled radar and sensing systems that help people understand what's happening in the world around them. By combining advanced radar, edge computing, and AI, we deliver situational awareness in environments where traditional sensing solutions struggle.
We're looking for a hands-on Machine Learning Engineer who enjoys turning cutting-edge ML research into production-ready software. You'll partner closely with our Data Scientists, taking new algorithms and implementing them in performant, maintainable, and scalable production systems. You'll also help build the ML infrastructure and tooling that accelerates future research, while ensuring our AI solutions are reliable enough for real-world deployment.

If you're technically curious, highly collaborative, and motivated by solving complex real-world problems, we'd love to talk.

What You'll Do

  • Partner with Data Scientists to transform research algorithms into robust, production-quality software.
  • Implement machine learning algorithms in high-performance C++ and Python with a focus on maintainability, scalability, and real-time performance.
  • Build and improve machine learning infrastructure, tooling, and training pipelines that enable faster experimentation and more efficient model development.
  • Design and implement AI agents, agentic workflows, and LLM-powered applications.
  • Deploy and maintain AI workloads across edge, near-edge, and cloud environments.
  • Collaborate across engineering and research teams to transition prototypes into production systems.

What We're Looking For

This position requires working directly or indirectly with the US Government in restricted environments. Candidates must be legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance in the future.'

This is NOT a fully remote position!

Required

  • BS, MS, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Machine Learning, AI, Robotics, or a related field.
  • Strong hands-on programming experience in C++ and Python.
  • 3-5 years of experience developing and deploying machine learning systems in production environments.
  • Experience building AI agents, LLM-based applications, or intelligent automation systems.
  • Strong problem-solving skills and ability to work across the full development lifecycle.
  • Excellent written and verbal communication and collaboration skills.

Someone Who Will Thrive in This Role

  • Enjoys solving difficult technical challenges that span algorithms, software, and deployment.
  • Enjoys bridging the gap between research and production, finding practical engineering solutions that make advanced ML usable in real-world products.
  • Takes ownership and drives projects from concept through production.
  • Continuously explores new AI, ML, and agentic technologies.
  • Works effectively across multidisciplinary teams.
  • Balances research innovation with practical product delivery.
  • Builds side projects, experiments with emerging AI tools, or enjoys hands-on technical exploration.

Bonus Points

  • Experience with radar, RF sensing, sensor fusion, computer vision, robotics, or autonomous systems.
  • Experience with LangChain, LangGraph, LlamaIndex, AutoGen, Semantic Kernel, or similar frameworks.
  • Experience optimizing models for edge deployment usingTensorRT, ONNX,OpenVINO, TVM, or similar tools.
  • Experience with embedded systems, GPUs, NPUs, FPGAs, or hardware acceleration.
  • Familiarity withMLOps, CI/CD, model monitoring, and large-scale production systems.

At MatrixSpace, Machine Learning Engineering is where advanced AI research becomes real-world capability. This is an engineering-heavy ML role focused on productionizing algorithms created by Data Scientists, with some ownership of the ML infrastructure that helps those Data Scientists move faster.