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Research Engineer Jobs in Washington (NOW HIRING)

Be a developer on the front line of the research, development, design, and deployment of an existing application * Responsible for designing, testing, coding, and developing solutions to meet ...

Be a developer on the front line of the research, development, design, and deployment of an existing application * Responsible for designing, testing, coding, and developing solutions to meet ...

Showing results 41-60

Research Engineer information

See Washington salary details

$41.9K

$120.1K

$161.4K

How much do research engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for research engineer in Washington is $120,069.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,800.00 and $117,800.00 per year, depending on experience, location, and employer.

What is a research engineer?

Research engineers are professionals who apply scientific and engineering principles to conduct research, develop new products, and improve existing technologies. They typically work in laboratories, research and development departments, or academic settings, collaborating with scientists and other engineers. Their work often involves designing experiments, analyzing data, and creating prototypes to solve technical problems or advance knowledge in their field.

Do I need a PhD to be a research engineer?

A PhD is not always required to become a research engineer, but it can be beneficial for roles involving advanced research, complex problem-solving, or specialized fields. Many research engineers hold a bachelor's or master's degree, along with relevant skills in programming, data analysis, and engineering tools. Industry experience and technical expertise are often equally important as formal education levels.

What is the difference between Research Engineer vs Data Scientist?

AspectResearch EngineerData Scientist
Required CredentialsTypically requires a master's or Ph.D. in engineering, computer science, or related fieldsUsually holds a master's or Ph.D. in statistics, computer science, or related areas
Work EnvironmentResearch labs, R&D departments, technology companiesData analysis teams, analytics departments, tech firms
Employer & Industry UsageUsed in engineering, manufacturing, aerospace, and tech industriesCommon in finance, healthcare, marketing, and tech sectors

Research Engineers focus on developing new technologies, prototypes, and engineering solutions, often working on hardware or system design. Data Scientists analyze large datasets to extract insights, build predictive models, and support decision-making. While both roles require strong technical skills and advanced degrees, their core functions and industry applications differ significantly.

What are the key skills and qualifications needed to thrive as a research engineer, and why are they important?

To thrive as a Research Engineer, a strong background in engineering principles, advanced mathematics, and scientific research—often supported by a relevant degree or postgraduate study—is essential. Familiarity with data analysis tools like MATLAB or Python, CAD software, and laboratory instrumentation is typically required, along with experience in technical report writing. Strong analytical thinking, creativity, and effective collaboration skills help Research Engineers excel in multidisciplinary teams. These competencies are vital for developing innovative solutions, advancing technology, and ensuring rigorous, impactful research outcomes.

How do research engineers typically collaborate with cross-functional teams during a project?

Research Engineers often work closely with scientists, data analysts, product managers, and software engineers to develop and implement innovative solutions. Collaboration usually involves regular meetings to align on project goals, sharing technical findings, and integrating research outcomes into product development. Effective communication and the ability to translate complex research concepts into actionable insights are key to ensuring the project progresses smoothly and meets its objectives.

What are the most commonly searched types of Research Engineer jobs in Washington?

The most popular types of Research Engineer jobs in Washington are:

What are popular job titles related to Research Engineer jobs in Washington?

For Research Engineer jobs in Washington, the most frequently searched job titles are:

What cities in Washington are hiring for Research Engineer jobs?

Cities in Washington with the most Research Engineer job openings:

Infographic showing various Research Engineer job openings in Washington as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $120,069 per year, or $57.7 per hour.

Senior Research Engineer, Threat Intelligence

Zoomcar

Washington, DC • On-site

$140 - $150/hr

Other

Medical, PTO

Posted 8 days ago


Job description

About the Role

You'll join STRIKE, SecurityScorecard's Threat Intelligence team, as the engineering counterpart to research. STRIKE runs several research motions in parallel, each on its own clock: rapid response to active events, longer product‑tied work, and standards‑anchored research on a quarterly cadence. The path from a finding to a shipped detection or feed gets reinvented every time. That’s the problem this role is here to solve.

You'll work directly with the senior technical leader who owns STRIKE’s R&D direction, and report to the Head of Threat Research for people management. Technical direction comes from R&D leadership; you own delivery. You'll take a research artifact (a malware finding, an infrastructure cluster, a new indicator class, a behavioral pattern) and turn it into something the company can use without a second round of engineering: schemas, pipeline hooks, distribution feeds, detection rules, or platform APIs.

This isn’t a pure research role, and it isn’t a pure platform role either. Researchers ideate, you ship.

Key Responsibilities Research‑to‑Production Pipeline
  • Own the path from research output to production‑ready artifact: a detection rule, a distributed feed, a scoring input, or a customer alert. Partner with adjacent teams to define clean handoff contracts, so new signals arrive downstream with the schema, value framing, and consumption pattern already defined.
Threat Intelligence Platform Engineering
  • Build and maintain STRIKE platform components across multiple services and runtimes, including distribution servers, sandbox orchestration, OSINT ingestion, federated sharing endpoints, agent runtimes, and rules engines that operate over standards‑anchored predicates. Extend these systems without breaking the data contracts already in production.
Detection Content and Signal Production
  • Turn research into shipped detection content: YARA, Sigma, STIX patterns, behavioral indicators, and the pipelines that distribute them. Build correlation pipelines that link scan data, attack surface signals, vulnerability data, and adversary tracking into customer‑facing intelligence.
Data Model and Standards Adoption
  • Drive STIX 2.1 adoption as a unified output schema and TAXII 2.1 as a distribution standard. Define and govern schemas that hold up once they reach downstream teams.
Research Workflow Engineering
  • Build the automation that removes commodity overhead from research work: indicator enrichment, report drafting, corpus correlation, feed normalization, and sandbox triage. Help move the team from analyst‑driven, model‑assisted workflows toward model‑driven workflows with analyst review.
  • The work that matters most here is often the unglamorous part: retrieval grounded in the team’s own corpus so outputs cite sources rather than model priors, schema‑constrained output so a generated indicator is a valid one, and eval harnesses that catch regressions before analysts do. Cost accounting, latency budgeting, prompt versioning, and output logging round out the infrastructure that makes a workflow safe to run unattended.
  • You should have a clear sense of when a model is the wrong tool. A regex beats a model for known patterns; a SQL query beats a model for structured data. Knowing where that line sits, and respecting it, is part of the job.
Cross‑Functional Delivery
  • Coordinate with engineering, measurement, and platform product teams so research actually lands in product. You’ll often serve as the engineering voice translating between researchers, product managers, and platform engineers, and you may occasionally explain the work to customers, journalists, or executives.
Qualifications Education
  • Bachelor’s or Master’s in Computer Science, Cybersecurity, or a related technical field. Self‑taught practitioners with strong public work are welcome.
Experience
  • 5 to 8 years in a hands‑on engineering role with meaningful exposure to threat intelligence, security research, or detection engineering. Prior experience building production systems that consume or emit threat intel data is required.
Technical Skills
  • Python and TypeScript/Node at a production level
  • Relational and cache data stores, plus at least one streaming or batch data platform
  • Cloud infrastructure (AWS preferred), containers, and CI/CD pipelines
  • Working knowledge of STIX 2.1, TAXII 2.1, MISP, and MITRE ATT\&CK, and how they work together in practice
Detection and Research Tooling

Hands‑on experience with YARA, Sigma, and STIX Patterning. Comfortable reading malware analysis output, parsing adversary infrastructure data, and writing detection logic that holds up under production load.

Applied Language Models

You’ve shipped production systems that use language models, not just demos. That includes retrieval over a real corpus, structured output with schema validation, eval harnesses that catch regressions before users do, and a solid understanding of where models fail: recency, long‑tail facts, numerical reasoning, and adversarial input or prompt injection. You can do the cost‑per‑task math for your workloads, and you can make the case when a smaller, tightly scaffolded model beats a larger one.

You approach model output with healthy skepticism by default. The bar for shipping a model‑generated indicator or detection is higher than for shipping a regex, and you understand why and design accordingly.

Bridge Mindset

You write code that ships, and you understand why researchers think the way they do. If you’ve only ever worked from a backlog handed down by a product manager, this probably isn’t the right fit. If you’ve taken an idea sketched out in a chat message and turned it into a deployed pipeline before the next sprint began, that’s the mode we’re looking for.

Bonus
  • Experience with policy‑as‑code or expression‑language engines (CEL, OPA, or similar)
  • Published or co‑authored security research (campaigns, vulnerabilities, adversary tracking)
  • Large‑scale telemetry experience (Splunk, Kinesis, NetFlow, or equivalent)
  • Contributor or maintainer on open‑source threat intel projects (MISP, OpenCTI, Sigma, STIX, ATT\&CK)
  • Familiarity with quantitative risk frameworks such as FAIR
  • Familiarity with Golang at a production level
Benefits

Specific to each country, we offer a competitive salary, stock options, health benefits, and unlimited PTO, parental leave, tuition reimbursements, and much more!

The estimated total compensation range for this position is $140,000 - $150,000 (base plus bonus). Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range. In addition to base salary, employees may also be eligible for annual performance‑based incentive compensation awards and equity, among other company benefits.

Equal Employment Opportunity

SecurityScorecard is committed to Equal Employment Opportunity and embraces diversity. We believe that our team is strengthened through hiring and retaining employees with diverse backgrounds, skill sets, ideas, and perspectives. We make hiring decisions based on merit and do not discriminate based on race, color, religion, national origin, sex or gender (including pregnancy) gender identity or expression (including transgender status), sexual orientation, age, marital, veteran, disability status or any other protected category in accordance with applicable law.

We also consider qualified applicants regardless of criminal histories, in accordance with applicable law. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact talentacquisitionoperations@securityscorecard.io.

Any information you submit to SecurityScorecard as part of your application will be processed in accordance with the Company’s privacy policy and applicable law.

SecurityScorecard does not accept unsolicited resumes from employment agencies. Please note that we do not provide immigration sponsorship for this position. #LI-DNI

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