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About This Role
##### Persons in these roles are expected to work from our offices in Seattle. On\-site requirements vary based on position and team. If you have questions about on\-site work arrangements for this role, please ask your recruiter.
##### Our base salary range is $146,880 \- $220,320, and in addition we have generous bonus plans to provide a competitive compensation package.
Who You Are:
To thrive as a Research Engineer at Ai2, you'll bring a blend of deep technical expertise and a collaborative, self\-directed mindset. You have extensive experience with deep learning and/or foundation models — whether through a PhD in ML or equivalent hands\-on industry work. You're a curious, agile engineer who can generate ideas, design experiments, and implement them in Python against real AI systems. You communicate research insights clearly to technical stakeholders, and you're energized by working with strong contributors toward shared, ambitious goals.
As a Research Engineer on the team, you'll be a core member responsible for training Ai2's flagship open models (e.g. Olmo, Molmo, and beyond). From system design to experiment release, you'll own end\-to\-end delivery while collaborating closely with research and engineering colleagues to push the boundaries of open model research.
Who We Are:
We are a non\-profit AI institute focused on developing foundational AI research and innovation to deliver real\-world positive impact through large\-scale open models, data, and artifacts (e.g., Olmo, Tulu, Molmo, FlexOlmo). Balancing academic freedom with corporate\-level scale (read about our new compute cluster here), Ai2 is uniquely resourced and positioned to deliver high\-impact, truly open research. Our team unites the best and brightest scientific and engineering minds to explore the potential of truly open AI. Through our efforts, including the pioneering Olmo and Molmo releases, we endeavor to empower academics, researchers, and AI developers more broadly to advance the science of language models, multimodal models, and generative AI.
If you are passionate about advancing the science of AI through open, rigorous research and believe in accessible AI for the common good, we want to hear from you!
Your Next Challenge:
Key responsibilities:
- Building and optimizing infrastructure for LLM, multimodal, and agentic research — including training/inference pipelines, dataset curation, and large\-scale preprocessing
- Designing, training, and evaluating multimodal models (vision \+ language) and agentic workflows, including tool use, planning, and long\-horizon tasks
- Scoping and leading research projects, prioritizing experiments for highest impact
- Bringing strong software engineering practices to a research environment and bridging cutting\-edge work to production\-quality products
- Contributing to and supporting the open\-source community through model releases, datasets, public APIs, and technical reports
What You'll Need:
- 4\+ years of ML infrastructure experience — data preprocessing, model training, evaluation, inference, and deployment
- Experience with end\-to\-end model development — dataset construction, training, fine\-tuning, evaluation, profiling, and monitoring
- Familiarity with modern model architectures — including LLMs (MoEs, long\-context models), vision\-language models (e.g., Molmo, LLaVA), and experience training and evaluating both
- Agentic systems knowledge — tools, memory, and long\-running workflows
- Strong software engineering fundamentals — performant, scalable systems and confident debugging
- Proficiency in Python and a major ML framework (PyTorch, JAX, or TensorFlow), with the flexibility to pick up new tools as needed
- Familiarity with cloud and containerization (e.g., GCP, AWS, Docker)
- Strong communication and collaboration skills — we're a small, close\-knit team and work best when everyone's pulling in the same direction
Education/Experience:
- BS or MSc in Computer Science, Statistics, Engineering, Applied Mathematics, or a related quantitative field (or equivalent experience)
- A minimum of 2 years of software development experience. (or equivalent experience)
Physical Demands and Work Environment:
The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.
- Must be able to remain in a stationary position for long periods of time.
- The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations.
- The ability to observe details at close range.
- Can work under deadlines.
A Little More About Ai2:
Ai2 is a Seattle based non\-profit AI research institute founded in 2014 by the late Paul Allen. Our mission is building breakthrough AI to solve the world's biggest problems. We develop foundational AI research and innovation to deliver real\-world impact through large\-scale open models, data, robotics, conservation, and beyond.
In addition to Ai2's core mission, we also aim to contribute to humanity through our treatment of each member of the Ai2 Team. Some highlights are:
- We are a learning organization – because everything Ai2 does is ground\-breaking, we are learning every day. Similarly, through weekly Ai2 Academy lectures, a wide variety of world\-class AI experts as guest speakers, and our commitment to your personal on\-going education, Ai2 is a place where you will have opportunities to continue learning alongside your coworkers.
- We value diversity \- We seek to hire, support, and promote people from all genders, ethnicities, and all levels of experience regardless of age. We particularly encourage applications from women, non\-binary individuals, people of color, members of the LGBTQA\+ community, and people with disabilities of any kind.
- We value inclusion \- We understand the value that people's individual experiences and perspectives can bring to an organization, and we are building a culture in which all voices are heard, respected and considered.
- We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave.
- We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures.
- We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, and we have so much else. We even have kayaks for you to paddle right outside our front door. We welcome interest from applicants from outside of the United States.
- We are friendly– chances are you will like every one of the 200\+ (and growing) people who work here. We do.
Ai2 is proud to be an Equal Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. You may view the related Know Your Rights compliance poster and the Pay Transparency Nondiscrimination Provision by clicking on their corresponding links.
This employer participates in E\-Verify and will provide the federal government with your Form I\-9 information to confirm that you are authorized to work in the U.S. If E\-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E\-Verify once you have accepted a job offer and completed the Form I\-9\.
We are committed to providing reasonable accommodations to employees and applicants with disabilities to the full extent required by the Americans with Disabilities Act (ADA). If you feel you need a reasonable accommodation pursuant to the ADA, you are encouraged to contact us at [email protected].
Benefits:
- Team members and their families are covered by medical, dental, vision, and an employee assistance program.
- Team members are able to enroll in our health savings account plan, our healthcare reimbursement arrangement plan, and our health care and dependent care flexible spending account plans.
- Team members are able to enroll in our company's 401k plan.
- Team members will receive $125 per month to assist with commuting or internet expenses and will also receive $200 per month for fitness and wellbeing expenses.
- Team members will also receive up to ten sick days per year, up to seven personal days per year, up to 20 vacation days per year and twelve paid holidays throughout the calendar year.
- Team members will be able to receive annual bonuses and can participate in the long\-term incentive plan.
Note: This job description in no way states or implies that these are the only duties to be performed by the team members(s) of this position. Team members will be required to follow any other job\-related instructions and to perform any other job\-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities. To perform this job successfully, the team member(s) will possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. The requirements listed in this document are the minimum levels of knowledge, skills, or abilities. This document does not create an employment contract, implied or otherwise, other than an at will relationship. *This position is located in Seattle, WA, USA. Exceptions are made on a case by case basis.*
Salary Context
This $146K-$220K range is below the median for Research Engineer roles in our dataset (median: $185K across 51 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 3,824 AI roles we're tracking, Research Engineer positions make up 2% of the market. At The Allen Institute for Artificial Intelligence, 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 Required
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 $260,000 based on 401 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($183K) sits 29% below the category median. Disclosed range: $146K to $220K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
The Allen Institute for Artificial Intelligence AI Hiring
The Allen Institute for Artificial Intelligence has 1 open AI role right now. They're hiring across Research Engineer. Based in Seattle, WA, US. Compensation range: $220K - $220K.
Location Context
AI roles in Seattle pay a median of $228,000 across 1,009 tracked positions. That's 14% above the national 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 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 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 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, 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 $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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