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Machine Learning Defense Jobs in Utah (NOW HIRING)

Deep hands-on machine learning and statistical modeling skills, including tree-based segmentation ... Experience inside a formal risk governance framework with three lines of defense, credit committee ...

Deep hands-on machine learning and statistical modeling skills, including tree-based segmentation ... Experience inside a formal risk governance framework with three lines of defense, credit committee ...

Deep hands- on machine learning and statistical modeling skills, including tree-based segmentation ... Experience inside a formal risk governance framework with three lines of defense, credit committee ...

Software Engineer II

Provo, UT ยท On-site

$92K - $126K/yr

Industry experience in defense? Not required -- we'll invest in you. If you meet the minimum ... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ...

Software Engineer II

Provo, UT ยท On-site

$92K - $126K/yr

Industry experience in defense? Not required -- we'll invest in you. If you meet the minimum ... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ...

Lead Software & Data Architect Engineer

Roy, UT ยท On-site

$136K - $231K/yr

... defense programs. These programs are demanding and complex, requiring creative solutions that ... Artificial intelligence and machine learning * Bachelor's degree in Computer Science, Data Science ...

$18 - $50/hr

... defense, and automotive industries. The intern will help create and manage engineering datasets ... Experience with Python, data analytics, machine learning, or AI technologies. * Familiarity with ...

Showing results 21-40

Machine Learning Defense information

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 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 popular job titles related to Machine Learning Defense jobs in Utah?

For Machine Learning Defense jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Machine Learning Defense jobs in Utah look for?

The top searched job categories for Machine Learning Defense jobs in Utah are:

What cities in Utah are hiring for Machine Learning Defense jobs?

Cities in Utah with the most Machine Learning Defense job openings:

Infographic showing various Machine Learning Defense job openings in Utah as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 22% Part Time, 2% Contract, and 1% Nights. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.

Defensive Cyber Operations (DCO) Analyst

Ogden, UT โ€ข On-site

Dark Wolf Solutions
IT Servicesย โ€ขย 51 - 200 employees

$90K - $145K/yr

Full-time, Contractor

Re-posted 4 days ago


Job description

Dark Wolf Solutions is looking for a Defensive Cyber Operations Analyst who will perform continuous system monitoring to identify malicious cyber-attacks while supporting the containment and remediation of IT threats. This role will function as an operator responsible for hands-on incident response, correlation, and threat detection both on-premise using ELK and across AWS GovCloud environments using Splunk Enterprise. Additionally, this position will leverage Artificial Intelligence (AI) and Machine Learning capabilities to enhance threat detection, streamline incident analysis, and accelerate response actions across monitored networks and applications. This role will be fully on-site at Hill AFB in Ogden, Utah. 

Key Responsibilities:

  • Active monitoring, detection, and analysis across on-prem (ELK) and cloud-hosted AWS GovCloud (Splunk Enterprise) environments. 
  • Utilize AI-assisted analysis, automation, and correlation of data from various log sources to triage security events, detect anomalies, and reduce response times for complex threats.
  • Vulnerability Management actions to include providing recommendations and implement mitigations. 
  • Conduct intrusion analysis and correlation of unauthorized activities; provide and implement recommendations to improve detection and customer mitigation processes. 
  • Participate in the Root Cause Analysis process and documentation capturing efforts taken to mitigate unauthorized actions.
  • Participate in the development of DCO tactics, techniques, and procedures (TTPs) and supporting documentation.
  • Identify security discrepancies and report and respond to security incidents. 
  • Provide research and analysis in support of expanding programs and areas of responsibility. 
  • Draft documentation for briefings, reports, and informational analyses. 
  • Participate in customer exercises (after duty hours may be required). 
  • Adhere to defined policies, master plans and schedules.
  • Complete all initial and annual training requirements and disclosures as outlined by BSTG. 
  • Perform all other duties as required, consistent with the goals, objectives, and responsibilities of the department. 

Required Qualifications:

  • 4+ years of relevant cybersecurity experience, including direct SOC / vSOC / CSSP incident response experience.
  • 2+ years of hands-on experience using Splunk Enterprise and ELK Stack (Elasticsearch, Logstash, Kibana) for event correlation and threat detection.
  • Direct experience monitoring, ingesting, and analyzing security telemetry within AWS GovCloud environments (e.g., CloudTrail, VPC Flow Logs, AWS GuardDuty).
  • Hands-on experience utilizing GitLab (e.g., source control, CI/CD pipelines, issue tracking, or DevSecOps workflows).
  • 2+ years of experience with employment of DoD cybersecurity requirements, policies, and procedures to include assessment and authorization activities.
  • Department of Defense Directive (DoDD) 8140 / 8570 IAT CSSP Certification must be obtained prior to hire (CEH, Security+, GCIH, CySA+ or Equivalent). 
  • Bachelor's degree in Computer Science, Information Technology, or a related field. 
  • US Citizenship and an active Top Secret/SCI security clearance required. 

Desired Qualifications:

  • Experience with AI/ML security tools (e.g., generative AI for query generation, automated threat intelligence, or AI-driven behavioral analytics).
  • AWS Certified Security – Specialty certification.
  • Splunk Core Certified Power User / Admin or Elastic Certified Analyst certifications.
  • Experience writing search queries using SPL (Splunk Processing Language) and KQL/Lucene (Kibana Query Language).
  • Experience with SentinelOne (or similar EDR platforms) for endpoint detection, threat hunting, and automated remediation.
  • Familiarity with Infrastructure-as-Code (IaC) tools such as Terraform or Ansible within a DevSecOps environment.
  • Experience performing cybersecurity activities in support of software and system requirements, design, development, testing, and sustainment. 
  • Experience with HBSS, ACAS, SCAP Compliance Checker (SCC), DISA STIGs. 
  • Working knowledge of NIST 800-53 Security and Privacy Controls. 
  • Experience with various operation systems such as RHEL and Windows. 
  • Experience in performing post-incident computer forensics without destruction of critical data. 
  • Ability to provide guidance on DoD Cyber regulations and requirements to engineering and software development staff. 

The estimated salary range for this role is $90,000.00 - $145,000.00, commensurate on experience and technical skillset. 

We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories.

In compliance with federal law, all persons hired will be required to verify identity, confirm US Citizenship, and complete the required employment eligibility verification upon hire.

We are strictly looking for direct, full-time W2 employees. We do not engage with third-party staffing agencies, C2C, or 1099 independent contractors for this role.