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About This Role
About Us
At Perceptronics, we develop advanced technologies to address national security challenges in areas including electronic warfare, autonomy, sensing, and intelligent systems. We combine artificial intelligence, machine learning, signal processing, optimization, and other computational methods to develop innovative solutions to difficult real-world problems.
Position Overview
Perceptronics is seeking an AI Research Scientist to join our research and development team. We are looking for candidates who enjoy solving difficult, often poorly defined technical problems and developing new algorithmic solutions.
We are interested in candidates from a range of technical backgrounds, including artificial intelligence, machine learning, signal processing, controls, operations research, applied mathematics, statistics, robotics, and related fields. The common thread is an ability to formulate technical problems, identify promising approaches, develop and evaluate algorithms, and improve those approaches based on experimental results and a deeper understanding of the problem.
Our work spans a broad range of methods, including statistical inference and estimation, clustering and density estimation, optimization, search and planning, tracking and filtering, signal processing, sensor fusion, machine learning, and related techniques. Machine learning is an important part of our work, but the appropriate solution to a problem may involve traditional algorithms, statistical methods, machine learning, or a combination of approaches.
We are particularly interested in candidates who can critically evaluate alternative approaches, understand their assumptions and limitations, and adapt or extend state-of-the-art academic research to solve real-world DoD problems.
Our application areas include electronic warfare, RF signal analysis, autonomy, unmanned systems, multi-agent systems, sensor systems, and other national security problems. Prior experience in one or more of these domains is highly valuable but is not required for candidates with strong algorithmic and research capabilities.
Requirements Key Responsibilities
- Investigate challenging technical problems and formulate algorithmic approaches for solving them.
- Perform literature reviews to identify promising methods, understand their strengths and limitations, and determine how they can be adapted to problems of interest.
- Design, implement, test, and improve prototype algorithms using techniques drawn from AI, statistics, optimization, estimation, search, signal processing, machine learning, and related fields.
- Analyze complex data and system behavior to understand underlying structure, identify meaningful patterns, and select appropriate computational approaches.
- Approach succeeds or fails.
- Compare alternative approaches and refine algorithms based on experimental results, theoretical insight, and operational requirements.
- Collaborate with scientists and engineers to integrate algorithms into operational software and hardware systems.
- Communicate technical approaches, experimental results, and recommendations to both technical and non-technical stakeholders.
- Stay current with relevant academic research and emerging methods and identify opportunities to apply them to Perceptronics problems.
Qualifications
- Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Electrical Engineering, Robotics, Applied Mathematics, Statistics, Operations Research, Controls, or a related technical field. An advanced degree is preferred.
- Strong foundation in algorithms and one or more areas such as probability and statistics, optimization, estimation, signal processing, control theory, search and planning, or machine learning.
- Experience developing algorithms in one or more areas such as statistical estimation, optimization, search and planning, controls, signal processing, tracking, sensor fusion, clustering, anomaly detection, or machine learning. Breadth across multiple areas is a strong plus.
- Ability to read and understand technical literature and translate research ideas into working algorithms.
- Strong critical-thinking and problem-solving skills, including the ability to reason about assumptions, tradeoffs, failure modes, and alternative approaches.
- Strong programming skills in Python, C++, or similar languages.
- Experience with scientific computing and machine learning libraries is beneficial, but we place greater emphasis on understanding and developing algorithms than on experience with any particular framework.
- Experience with electronic warfare, RF signal processing, autonomy, robotics, unmanned systems, multi-agent systems, tracking, sensing, or related defense applications is highly desirable but not required.
- Excellent communication skills and the ability to work effectively as part of a collaborative technical team.
- U.S. citizenship and willing to obtain a security clearance required.
Why Join Us?
- Work on challenging technical problems where research and creative problem solving directly contribute to operational capabilities.
- Apply a broad range of algorithms and computational techniques rather than being limited to a single technology or methodology.
- Work with a small, collaborative team of scientists and engineers on problems spanning AI, electronic warfare, autonomy, sensing, and advanced algorithms.
- Opportunities for professional development and growth in rapidly evolving technical areas.
- Because Perceptronics is a member of the Pacific Defense group of companies, our growth is accelerating and there is ample room for career growth.
- Competitive salary and benefits package.
Benefits
We offer competitive salaries, and great benefits including a top health insurance policy with employee's premium 100% covered, a generous PTO policy, and flexible work schedule. Perceptronics Solutions is an Equal Opportunity Employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity or expression, age, disability, veteran status, or any other protected factor.
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 9,653 AI roles we're tracking, Research Scientist positions make up 2% of the market. At Pacific Defense, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills Required
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 708 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Pacific Defense AI Hiring
Pacific Defense has 1 open AI role right now. They're hiring across Research Scientist. Based in Fairfax, VA, US.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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