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About This Role
About Avalyn:
Avalyn aims to transform the treatment paradigm for pulmonary fibrosis and other serious, rare respiratory diseases. The company is advancing optimized inhaled formulations of established antifibrotic medicines designed to deliver drug directly to the lungs, enhance local efficacy, and reduce systemic side effects. Avalyn's AP01 program is an optimized inhaled formulation of pirfenidone currently being evaluated in MIST, a global Phase 2b clinical trial in patients with progressive pulmonary fibrosis (PPF). AP01 has demonstrated encouraging safety and clinical activity across Phase 1b and an ongoing, multi-year open-label extension trial, with long-term data supporting the potential to preserve lung function while improving tolerability relative to historical oral pirfenidone. Avalyn's AP02 program is an optimized inhaled formulation of nintedanib currently being evaluated in AURA, a global Phase 2 clinical trial in patients with idiopathic pulmonary fibrosis (IPF). Avalyn is also advancing AP03, an inhaled fixed-dose combination of pirfenidone and nintedanib, designed to deliver multiple antifibrotic mechanisms through a single lung-targeted platform. By leveraging its proprietary drug-device approach and deep expertise in rare respiratory disease development, Avalyn aims to establish a new standard of care in pulmonary fibrosis through inhaled, lung-targeted therapies. For more information, please visit avalynpharma.com and follow the company on LinkedIn.
Position Summary:
The Director, Clinical Development Research Scientist will report to the Senior Vice President, Clinical Development and serve as a key clinical and scientific leader advancing Avalyn's IPF/ILD clinical development programs. This individual will provide therapeutic-area expertise and strategic leadership across the development lifecycle, from program and study strategy through protocol design, clinical execution, data interpretation, regulatory interactions, and development planning.
The Director will lead one or more clinical trials and partner closely with Clinical Operations, Biostatistics, Regulatory Affairs, Pharmacovigilance, Translational Science, Data Management, CMC, and other functions to ensure clinical trial activities are scientifically rigorous, patient-focused, operationally feasible, and aligned with broader program objectives.
This individual will help shape development strategy, including study design, endpoints, development sequencing, risk assessment, data interpretation, and program-level decision-making. The Director will also provide medical and scientific expertise across multiple studies, serve as a resource to investigators and external experts, and contribute to regulatory interactions, advisory boards, publications, and scientific presentations.
The successful candidate will bring a balance of strategic thinking and hands-on clinical development expertise, with the ability to translate emerging clinical data into actionable development decisions.
Responsibilities:
Clinical Development Strategy & Program Leadership
- Provide clinical and scientific expertise for Avalyn IPF/ILD programs and contribute to broader portfolio and development strategy.
- Develop and refine clinical trial strategies, including study sequencing, objectives, endpoints, patient populations, and overall program design.
- Lead cross-functional development discussions and evaluate program risks, opportunities, and development alternatives to inform study design, sequencing, and resource priorities.
- Provide strategic clinical input into development plans, target product profiles, and key program milestones.
Study Design & Clinical Trial Leadership
- Lead protocol development, including study objectives, endpoints, eligibility criteria, safety monitoring, and risk mitigation.
- Provide clinical and scientific leadership across multiple studies, ensuring consistency and scientific rigor across the development program.
- Contribute to statistical analysis plan assumptions and assess the clinical relevance and interpretability of statistical approaches.
- Provide clinical oversight into study feasibility, investigator/site selection, protocol amendments, and study-level development decisions.
- Partner with Clinical Operations and CROs to support effective study execution while maintaining scientific integrity and patient safety.
Medical Oversight, Safety & Data Interpretation
- Serve as an IPF/ILD disease-area expert and provide medical guidance across assigned programs.
- Provide medical oversight to study teams and Medical Monitors, including assessment of patient safety, clinical risk, and disease-specific considerations.
- Lead clinical data reviews and interpret emerging safety and efficacy data across studies.
- Identify cross-study trends and translate findings into clinical and development recommendations.
- Partner with Biostatistics, Data Management, Pharmacovigilance, and Translational Science on data review, interpretation, and benefit-risk assessment.
Clinical Documentation & Regulatory
- Provide clinical and scientific leadership in the development and review of protocols, Investigator Brochures, Clinical Study Reports, briefing documents, and regulatory submissions.
- Lead Clinical Study Report (CSR) authoring and ensure appropriate clinical interpretation of study findings.
- Support FDA and other health authority interactions, including EOP2 meetings and responses to regulatory questions.
- Contribute to regulatory strategy and translate clinical data and program strategy into clear, scientifically rigorous regulatory narratives.
Cross-Functional & External Leadership
- Serve as a senior clinical leader on multidisciplinary development teams and provide clear recommendations to senior leadership.
- Build strong relationships with investigators, KOLs, external experts, CROs, and other external partners.
- Provide clinical and scientific leadership at investigator meetings, advisory boards, and other external forums.
- Support identification and engagement of clinical experts and investigators to inform program strategy and trial design.
Scientific Communications
- Contribute to publication strategy and external dissemination of clinical development data.
- Lead or support abstracts, posters, manuscripts, presentations, and scientific publications.
- Present clinical development strategy and emerging data at investigator meetings, advisory boards, scientific congresses, and other external forums.
- Maintain awareness of evolving IPF/ILD literature, treatment paradigms, competitive developments, and standards of care.
Qualifications:
- Advanced clinical or scientific degree (e.g., DNP, APRN, MD, PhD or equivalent) with significant clinical research, clinical development, or relevant therapeutic-area experience.
- 7–10+ years of experience in clinical research, clinical development, drug development, or a related field, including meaningful sponsor-side experience.
- Deep expertise in IPF, ILD, or pulmonary medicine, , with a strong understanding of the treatment landscape and unmet patient needs.
- Demonstrated experience leading or contributing to Phase 2 and/or Phase 3 clinical trials, including strong experience in protocol development, clinical trial strategy, safety monitoring, and risk mitigation.
- Demonstrated ability to interpret clinical safety and efficacy data and translate findings into evidence-based, program-level development decisions.
- Experience contributing to clinical development strategy across multiple studies and/or development stages, with the ability to connect study-level decisions to broader program, portfolio, and product objectives.
- Working knowledge of ICH-GCP and global regulatory requirements, with experience supporting health authority interactions and clinical/regulatory documentation.
- Demonstrated experience managing, mentoring, and developing clinical development professionals, with strong leadership and influencing skills and the ability to build high-performing teams.
- Excellent communication and collaboration skills, with the ability to engage effectively with investigators, KOLs, regulatory agencies, senior leadership, and cross-functional stakeholders.
- Strong scientific and clinical judgment, with the ability to evaluate benefit-risk considerations, make clear recommendations, and influence decisions across the organization.
- Ability to operate effectively in a fast-paced environment while balancing strategic responsibilities with hands-on clinical development activities.
- Willingness to travel as needed for investigator meetings, advisory boards, site visits, scientific conferences, and other clinical development activities.
- Ability and willingness to travel up to 25% domestic and international
Salary Context
This $220K-$242K range is above the 75th percentile for Research Scientist roles in our dataset (median: $199K across 63 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 9,079 AI roles we're tracking, Research Scientist positions make up 2% of the market. At Avalyn Pharma, 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 749 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,300. Disclosed range: $220K to $242K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Avalyn Pharma AI Hiring
Avalyn Pharma has 1 open AI role right now. They're hiring across Research Scientist. Based in Boston, MA, US. Compensation range: $242K - $242K.
Location Context
AI roles in Boston pay a median of $215,000 across 360 tracked positions.
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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, 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 $256,000 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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