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Overview:
Come join a company that strives for *Extraordinary People and Exceptional Performance*! Chenega Professional \& Technical Services, a Chenega Professional Services’ company, is looking for a Research Scientist I – Virology to support the United States Army Medical Research Institute of Infectious Diseases (USAMRIID).
The Research Scientist I – Virology provides advanced scientific and technical support to virology research programs focused on viral pathogenesis and evaluation of medical countermeasures, including vaccines, antibody\-based therapeutics, and antiviral drugs. This role supports in vivo and in vitro studies, develops and applies advanced immunological and molecular biology assays, and operates in high\-containment laboratory environments (BSL\-2, BSL\-3, and BSL\-4\).
Our company offers employees the opportunity to join a team where there is a robust employee benefits program, management engagement, quality leadership, an atmosphere of teamwork, recognition for performance, and promotion opportunities. We actively strive to channel our highly engaged employee’s knowledge, critical thinking, innovative solutions for our clients.
Responsibilities:
- Serve as a mentor in BSL\-3 and BSL\-4 laboratory environments.
- Coordinate and collaborate with scientists within the Division and Institute on in vivo and in vitro studies evaluating medical countermeasures against infectious diseases.
- Support approximately ten (10\) small animal studies across BSL\-2, BSL\-3, and BSL\-4 laboratories, including autonomous execution of downstream analyses.
- Perform assessments of viral replication using plaque assays and RT\-qPCR; conduct transcriptomic analyses (spatial, single\-cell, and/or bulk); evaluate blood chemistry; and measure viral antigens, antiviral antibodies, cytokines, and chemokines using Luminex and ELISA platforms.
- Design, implement, and maintain in vitro cell culture systems, including single\-cell cultures and micro physiological systems such as organoids and organs\-on\-a\-chip.
- Plan, manage, and execute complex in vitro studies to evaluate viral pathogenesis, replication, and medical countermeasure efficacy; review, organize, analyze, and report study data to the Principal Investigator (PI).
- Perform molecular biology techniques including PCR, qRT\-PCR, cloning, transformations, fluorescence in\-situ hybridization (FISH), flow cytometry, Western blotting, immunofluorescence assays (IFAs), high\-content imaging, plaque assays, PRNTs, and related methodologies.
- Conduct routine and advanced cell culture activities, including cryopreservation, thawing of cell lines, transfection, protein and antibody purification, and viral stock production and characterization.
- Present protocols and research data at weekly virology meetings.
- Assess, manage, and maintain laboratory supplies in BSL\-2, BSL\-3, and BSL\-4 laboratories, including ordering through GFEBS and/or DMLSS systems.
- Perform technical literature reviews and assist in the preparation of proposals, technical reports, and peer\-reviewed manuscripts; may present work at scientific meetings requiring CONUS or OCONUS travel.
- Ensure accountability, management, safeguarding, and storage of BSAT, animal tissue samples, and working stock samples, maintaining required records for FSAP\-registered Principal Investigators.
- Assist with annual equipment inventory management in BSL\-2, BSL\-3, and BSL\-4 laboratories.
- Provide a monthly PI Technical Report to the TPOC no later than the last working day of each month.
- Perform other duties as assigned in support of virology research operations
Qualifications:
- Master’s degree in biomedical science, microbiology, virology, or a related scientific discipline.
- Minimum of five (5\) years of post\-degree laboratory experience in virology or related biomedical research.
- Demonstrated experience with immunological assays, including Luminex, ELISA, flow cytometry, and ELISPOT.
- Demonstrated experience designing, developing, and using micro physiological systems for viral research.
- Ability to work in BSL\-2, BSL\-3, and BSL\-4 laboratory environments.
- Eligibility for and ability to maintain BPRP and CS\-PRP enrollment in accordance with contract requirements and applicable regulations.
- Active Secret clearance or ability to obtain and maintain one.
*Preferred Qualifications:** Experience supporting antiviral vaccine and therapeutic development programs.
- Experience with transcriptomic analyses (single\-cell, spatial, or bulk).
- Experience presenting scientific data at professional or scientific meetings.
*Knowledge, Skills and Abilities:** Strong knowledge of virology, viral pathogenesis, and medical countermeasure evaluation.
- Proficiency in advanced molecular biology, immunology, and cell culture techniques.
- Ability to independently analyze complex scientific data and clearly communicate results.
- Strong collaboration and communication skills within multidisciplinary research teams.
- Ability to comply with strict biosafety, security, and regulatory requirements.
Teleworking Permitted?: false Teleworking Details: No telework, inclement weather telework only. Estimated Salary/Wage: USD $75,000\.00/Yr. Up to USD $90,000\.00/Yr.
Salary Context
This $75K-$90K range is in the lower quartile for Research Scientist roles in our dataset (median: $183K across 109 roles with salary data).
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 3,823 AI roles we're tracking, Research Scientist positions make up 3% of the market. At Chenega Corporation, 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 in Demand for This Role
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 $223,400 based on 280 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($82K) sits 63% below the category median. Disclosed range: $75K to $90K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Chenega Corporation AI Hiring
Chenega Corporation has 5 open AI roles right now. They're hiring across Data Scientist, AI/ML Engineer, Research Scientist. Positions span Arlington, VA, US, Springfield, VA, US, Fort Detrick, MD, US. Compensation range: $90K - $90K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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