Interested in this Research Engineer role at Clarity Innovations, LLC?
Apply Now →About This Role
Clarity Innovations is a trusted national security partner, dedicated to safeguarding our nation’s interests and delivering innovative solutions that empower the Intelligence Community (IC) and Department of Defense (DoD) to transform data into actionable intelligence, ensuring mission success in an evolving world.
Our mission-first software and data engineering platform modernizes data operations, utilizing advanced workflows, CI/CD, and secure DevSecOps practices. We focus on challenges in Information Warfare, Cyber Operations, Operational Security, and Data Structuring, enabling end-to-end solutions that drive operational impact.
We are committed to delivering cutting-edge tools and capabilities that address the most complex national security challenges, empowering our partners to stay ahead of emerging threats and ensuring the success of their critical missions. At Clarity, we are people-focused and set on being a destination employer for top talent, offering an environment where innovation thrives, careers grow, and individuals are valued. Join us as we continue to lead innovation and tackle the most pressing challenges in national security.
Principal Security Researcher
Discipline: Reverse Engineering / Vulnerability Research
Location: Rome, NY
Clearance: Secret with the ability to obtain and maintain TS/SCI
Company Overview
Clarity Innovations equips customers with the technology, expertise, and support needed to conduct successful cyber operations. We bring together talented engineers, researchers, and operators to solve some of the U.S. Government’s most challenging technical problems. Our teams combine technical excellence, creativity, and collaboration to deliver capabilities that advance customer missions.
Role
Clarity Innovations is seeking a Senior Principal Security Researcher to independently execute complex vulnerability research and reverse engineering assignments. You will investigate system behavior, identify weaknesses, and develop reproducible demonstrations of their impact within customer-authorized research activities.
You will own defined research efforts from planning through delivery, select appropriate analysis methods, and adjust approaches as evidence develops. Your contributions will significantly affect research outcomes and may influence departmental results. The role requires practical technical knowledge, collaboration within and occasionally outside the research team, and the ability to recommend improvements and assist junior researchers.
Responsibilities
- Independently plan and execute assigned research efforts, define milestones, assess feasibility, and deliver results aligned with customer priorities.
- Perform static and dynamic analysis using disassemblers, debuggers, emulators, tracers, and fuzzers.
- Identify vulnerabilities, conduct root-cause analysis, and document reproducible findings and technical limitations.
- Develop reliable proof-of-concept exploits and operational exploit components for authorized customer requirements; evaluate and bypass relevant mitigations.
- Adjust research tools and processes, and recommend enhancements that improve the effectiveness of the research team.
- Build reusable tooling and automation to accelerate discovery, analysis, and validation.
- Communicate progress, risks, findings, and recommendations to technical and non-technical stakeholders; share results externally when authorized.
- Collaborate within and occasionally outside the research team to resolve dependencies and build support for research approaches.
- Provide guidance and assistance to junior researchers, participate in peer reviews, and coordinate technical tasks within assigned efforts.
Minimum Qualifications
- Secret security clearance with the ability to obtain and maintain a TS/SCI security clearance; U.S. citizenship is required.
- Bachelor’s degree in Computer Engineering, Computer Science, Software Engineering, or a related technical discipline, or equivalent experience, and a minimum of 5 years of prior relevant experience.
- Demonstrated ability to independently conduct vulnerability research and reverse engineering, taking defined investigations from planning through documented results.
- Experience using Ghidra, Binary Ninja, IDA, or comparable reverse engineering and disassembly tools.
- Strong knowledge of Linux fundamentals, including sockets, file descriptors, networking, iptables, file systems, and kernel behavior; ability to troubleshoot basic networking issues.
- Ability to read and write C and analyze assembly for architectures such as ARM, MIPS, or x86-64.
- Strong programming fundamentals, including networking, data structures, and data models.
- Practical experience with exploitation techniques such as arbitrary read/write primitives, shellcode development, return-oriented programming, or jump-oriented programming.
- Experience adjusting research methods or recommending tooling and process improvements to solve technical problems.
- Ability to collaborate across technical boundaries, explain findings clearly, and provide guidance to less experienced contributors.
- Experience participating in capture-the-flag competitions, hackathons, or other cybersecurity competitions.
Preferred Qualifications
- Active Top Secret security clearance.
- Experience reverse engineering operating systems and kernels.
- Experience with AFL++ or libFuzzer and security mechanisms such as SELinux, seccomp, ASLR, and control-flow integrity.
- Experience with GDB, gdbserver, compiler toolchains, and the Android Native Development Kit.
- Experience using QEMU or Unicorn to emulate code in non-native environments.
- Demonstrated experience discovering previously unknown vulnerabilities, including zero-days.
- Experience coordinating a research workstream, reviewing peers’ findings, or mentoring junior researchers.
Salary Range: $145,900 - $248,000
Pay Range
The posted pay range reflects the anticipated base salary range for this position and is provided to give candidates a general understanding of the compensation opportunity. The actual salary offered will be determined based on the requirements of the position and a variety of job-related factors, which may include geographic location, applicable Federal Government contract labor categories and wage rates, relevant experience, skills and competencies, education, certifications, and the scope and responsibilities of the role.
Because this position may be performed in multiple locations and may be subject to different contract requirements, the salary ultimately offered may vary based on the applicable location and contract. The posted range is not a guarantee of a specific starting salary or an indication that an offer will be made at any particular point within the range.
Total Rewards
In addition to competitive base pay, Clarity provides a Total Rewards package designed to attract and retain exceptional professionals committed to excellence. Our benefits reflect the value we place on skilled individuals who drive our impact in critical digital missions.
At Clarity, a career means joining a high-performing team advancing vital work in the digital landscape. We encourage you to consider the total value of joining us—competitive compensation, comprehensive benefits, and resources that support your growth and impact.
Our Total Rewards package includes performance-based bonuses, extensive medical, dental, and vision coverage, a 401(k) plan with company match, substantial paid time off and holidays, flexible work arrangements where possible, and a range of income protection benefits. We are committed to supporting your well-being, professional growth, and ability to contribute to essential digital missions.
We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
Salary Context
This $145K-$248K range is above the median for Research Engineer roles in our dataset (median: $185K across 72 roles with salary data).
View full Research Engineer salary data →Role Details
About This Role
Research Engineers bridge the gap between research and production. They implement papers, build experiment infrastructure, optimize training pipelines, and make research prototypes production-ready. They're the engineers who make research work at scale.
The role sits at a unique intersection. You need to understand the math well enough to implement novel architectures correctly, and you need the engineering chops to make them run efficiently on distributed systems. When a research scientist has a breakthrough idea, you're the person who turns it from a notebook prototype into a training pipeline that runs on 256 GPUs.
Across the 11,520 AI roles we're tracking, Research Engineer positions make up 2% of the market. At Clarity Innovations, LLC, this role fits into their broader AI and engineering organization.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
What the Work Looks Like
A typical week involves: implementing a new attention mechanism from a recent paper, profiling and optimizing a training pipeline that's bottlenecked on data loading, building evaluation infrastructure for a new benchmark, debugging distributed training issues across a GPU cluster, and pair-programming with a research scientist on their latest experiment. The work is deeply technical.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
Skills in Demand for This Role
Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.
Experience with large-scale training infrastructure (FSDP, DeepSpeed, Megatron), GPU programming (CUDA, Triton), and the internals of ML frameworks (PyTorch internals, custom autograd functions) is what makes candidates stand out. The best research engineers can debug issues that span the full stack from GPU memory management to numerical precision to algorithmic correctness.
Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
Compensation Benchmarks
Research Engineer roles pay a median of $252,000 based on 476 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($196K) sits 22% below the category median. Disclosed range: $145K to $248K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Clarity Innovations, LLC AI Hiring
Clarity Innovations, LLC has 1 open AI role right now. They're hiring across Research Engineer. Based in Rome, NY, US. Compensation range: $248K - $248K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 median).
Career Path
Common paths into Research Engineer roles include Software Engineer, ML Engineer, Research Intern.
From here, career progression typically leads toward Senior Research Engineer, Research Scientist, ML Architect.
This is one of the best entry points into AI research without a PhD. Build a strong engineering portfolio with ML projects, contribute to open-source ML frameworks, and demonstrate that you can implement complex ideas correctly and efficiently. The transition to Research Scientist is possible with published first-author work, which some research engineer roles support.
What to Expect in Interviews
Technical screens test both engineering skill and research understanding. Expect coding rounds with performance-critical implementations (GPU optimization, efficient data loading). Be prepared to discuss papers relevant to the team's research area and explain how you'd implement key ideas. System design questions focus on training infrastructure: distributed training, experiment tracking, and compute resource management.
When evaluating opportunities: Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
AI Hiring Overview
The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
The AI Job Market Today
The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (140) are outnumbered by mid-level (5,630) and senior (4,176) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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