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Remote Failure Analysis Engineer Jobs in Washington

We're a remote-first culture with operations in North America, Europe, the Middle East, and APAC ... analysts. Responsibilities : * Apply clustering, classification, anomaly detection, and other ...

This is a fully remote position for candidates in the continental U.S., with work hours aligned to ... Review and analyze software runtime performance, making algorithmic and performance improvements.

Senior Software Engineer (Command & Control)

Reston, VA ยท On-site +1

$127K - $168K/yr

Remote Sensing (the data), Space Systems (the components), and Mission Solutions (the platforms ... Improve system resilience by identifying and addressing failure modes, bottlenecks, and operational ...

Senior Software Engineer (Command & Control)

Arlington, VA ยท On-site +1

$141K - $186K/yr

Remote Sensing (the data), Space Systems (the components), and Mission Solutions (the platforms ... Improve system resilience by identifying and addressing failure modes, bottlenecks, and operational ...

Red Teaming Fellowship

Washington, DC ยท On-site +1

$32.50/hr

... engineers, and subject-matter experts to identify vulnerabilities, uncover failure modes, and ... Analyze model behavior and document findings in clear, actionable reports * Support the development ...

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Showing results 1-20

Remote Failure Analysis Engineer information

What is the difference between Remote Failure Analysis Engineer vs Remote Quality Engineer?

AspectRemote Failure Analysis EngineerRemote Quality Engineer
CredentialsBachelor's in Engineering, certifications in failure analysis or reliabilityBachelor's in Engineering, certifications in quality management or Six Sigma
Work EnvironmentLaboratory, technical analysis, remote troubleshootingProcess audits, quality control, remote data analysis
Industry UsageElectronics, manufacturing, aerospaceManufacturing, electronics, automotive
Search & Comparison IntentUnderstanding failure analysis roles, technical skillsQuality assurance, process improvement roles

The Remote Failure Analysis Engineer focuses on diagnosing product failures through technical analysis, often involving lab work and remote troubleshooting. In contrast, the Remote Quality Engineer emphasizes maintaining quality standards, process improvements, and data analysis. Both roles require engineering backgrounds and certifications but serve different functions within manufacturing and electronics industries.

What are the most commonly searched types of Failure Analysis Engineer jobs in Washington? The most popular types of Failure Analysis Engineer jobs in Washington are:
What are popular job titles related to Remote Failure Analysis Engineer jobs in Washington? For Remote Failure Analysis Engineer jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Remote Failure Analysis Engineer jobs in Washington look for? The top searched job categories for Remote Failure Analysis Engineer jobs in Washington are:
What cities in Washington are hiring for Remote Failure Analysis Engineer jobs? Cities in Washington with the most Remote Failure Analysis Engineer job openings:
Infographic showing various Remote Failure Analysis Engineer job openings in Washington as of June 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Staff ML Application Engineer

Dragos, Inc.

Hanover, MD โ€ข Remote

$225K/yr

Other

Posted 9 days ago


Job description

Dragos is on a relentless mission to defend industrial organizations that provide us with the necessities of modern civilization; running water, functioning electricity, and safe industrial working environments. As the market leader in ICS/OT Cybersecurity, we are dedicated to arming our customers with best-in-class technology, threat intelligence, and services to protect their systems as effectively and efficiently as possible. We're a remote-first culture with operations in North America, Europe, the Middle East, and APAC. We're looking for mission-oriented teammates who embody our core values of authenticity, transparency, and trust. Are you ready to make a difference? Come join a mission that can save the world!

About the Role:

We're looking for a Machine Learning Application Engineer to join our Engineering team. This role sits at the intersection of data engineering and applied ML. You'll be taking existing model types and putting them to work inside our product and data pipelines. You won't be training models from scratch or managing ML infrastructure, but you will be doing the thoughtful applied work of figuring out which techniques fit which problems, wiring them into our workflows, and making sure the outputs are reliable and useful.

You'll work closely with AI Engineers, Data Engineers, and product teams to bring ML-driven capabilities into the Dragos platform. Things like clustering network behaviors, classifying assets, and surfacing anomalies that matter for ICS/OT security analysts.

Responsibilities:

  • Apply clustering, classification, anomaly detection, and other established ML techniques to cybersecurity data problems in the ICS/OT domain.
  • Integrate ML model outputs into existing data pipelines and product workflows, supporting both batch and near-real-time processing patterns.
  • Understand model behavior and translate research outputs into reliable pipeline components.
  • Work with Data Engineers to ensure ML-driven stages of the pipeline have clear data contracts, appropriate observability, and sane failure modes.
  • Evaluate open-source and third-party models for fit against specific use cases, knowing when to apply an existing tool versus when to escalate to a model-building effort.
  • Write clean, maintainable Python or Rust that other engineers can reason about, test, and extend.
  • Troubleshoot ML component behavior in production to diagnose issues with output quality, data drift, or unexpected edge cases.
  • Communicate clearly about what a model is doing, where it's uncertain, and how its outputs should (and shouldn't) be used downstream.

Qualifications:

  • 4+ years of software engineering experience, with meaningful time spent working with ML outputs or data pipelines in a production context.
  • Strong Python skills; SQL proficiency; comfort reading and reasoning about data at scale.
  • Hands-on experience applying ML techniques including clustering (k-means, DBSCAN, hierarchical), classification, and anomaly detection.
  • Familiarity with scikit-learn and the surrounding Python ML ecosystem; you don't need to have implemented a neural net, but you should know how to use one responsibly.
  • Solid understanding of data pipeline concepts: how data flows, where it gets transformed, what can go wrong, and how to make failures visible.
  • Ability to evaluate whether a model's outputs are actually trustworthy for a given use case - not just whether accuracy metrics look good.
  • Strong written and verbal communication; comfortable explaining tradeoffs to both technical and non-technical stakeholders.
  • Cybersecurity domain knowledge - especially around threat detection, network behavior, or ICS/OT operations is a meaningful plus, but not a prerequisite.

Nice to Have:

  • Experience working with graph-based representations of network topology or asset relationships.
  • Familiarity with stream processing or event-driven architectures.
  • Exposure to containerized environments (Docker, Kubernetes) as a consumer/deployer, not necessarily an operator.

Compensation:

  • Salary: $225,000.00
  • Competitive Equity Package
  • Comprehensive Benefits Plan

#LI-JF1 #LI-REMOTE

#LI-NH1 #LI-REMOTE

Dragos is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, state, or local laws. All new hires must pass a background check as a condition of employment.