Senior Research Engineer, Olmo + Molmo

Ai2; Seattle (WA); On-site; USD 146,880 - 220,320; Full time

Benefits offered by this job

Health, dental, and vision coverage

401k plan

$125 monthly for commuting/internet

$200 monthly for fitness expenses

Up to 20 vacation days and sick days

Job summary

Ai2 is seeking a Research Engineer in Seattle, offering a competitive salary range of $146,880–$220,320 plus bonuses. The ideal candidate will have strong expertise in deep learning, extensive experience with ML infrastructure, and solid software engineering skills.

Your role includes building infrastructure for research, designing multimodal models, and contributing to open-source projects. Benefits include comprehensive healthcare, a 401k plan, and generous vacation policy.

Qualifications

• 4+ years of ML infrastructure experience — data preprocessing, model training, evaluation, inference, deployment.
• Experience with end-to-end model development — dataset construction to monitoring.
• Knowledge of modern model architectures including LLMs and vision-language models.

Responsibilities

• Build and optimize infrastructure for LLM and multimodal research.
• Design, train, and evaluate multimodal models.
• Scope and lead research projects for high impact.

Skills

Deep learning expertise

Python

ML infrastructure experience

Software engineering fundamentals

Communication skills

Containerization (e.g., Docker)

Familiarity with GCP or AWS

Education

BS or MSc in Computer Science

Minimum 2 years of software development experience

Tools

PyTorch

JAX

TensorFlow

Job description

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.

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.

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

Qualifications

• 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 and 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

• 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.

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.

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 [e-mail].

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.