AI Researcher Jobs in Washington
AI Researcher jobs in Washington are among the most actively recruited roles in the country, concentrated in Seattle's technology corridor and anchored by a dense cluster of machine learning, natural language processing, and computer vision work at companies ranging from new graduates through principal-level researchers. Seattle, Redmond, and Bellevue account for the majority of openings, with major employers like Microsoft, Amazon, and Apple maintaining large research teams in the region. Demand is especially strong in foundation model development, reinforcement learning, and applied AI systems. Find a role that fits below and apply directly.
Find AI Researcher JobsOverview
Showing 5 of 33+ AI Researcher jobs
Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you'll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world.
DigitalOcean is building the Agentic Inference Cloud — anchored by Inference Engine, our model-serving platform — to help fast-growing AI-native companies start, scale, and optimize agentic workloads. Applied Research is the layer that generates the proprietary science that compounds across that platform: routing that learns instead of following static rules, memory that improves recall and personalization, observability that explains why agents succeed or get stuck, and reinforcement learning that closes the loop between production signals and model behavior.
We're hiring a Director of Research to build and lead this function: set the research agenda, grow the team, and make sure the science this group produces ships into real product outcomes — better model selection and routing, more reliable agents, lower cost and latency, and higher task-success rates for the developers and enterprises running agentic workloads on DigitalOcean.
This is a hybrid role by design: enough technical depth to personally evaluate and shape research direction across routing, memory, observability, and RL, and enough leadership range to build a team, prioritize against a roadmap, and defend research investment to product and executive stakeholders.
What You'll Do
Set the research agenda
- Define and own the applied research roadmap across adaptive routing (evolving model selection from static rules into a system that learns from real usage, cost, and latency), memory (retrieval quality and durable recall for long-running agents), agent observability (understanding when agents make progress, get stuck, or make mistakes), and reinforcement learning / closed-loop learning (turning production feedback into better models and policies).
- Track emerging model architectures and specialized, domain-tuned model approaches, and translate what's relevant into DigitalOcean's product roadmap.
- Keep the agenda tightly coupled to product outcomes — every research bet should map to a measurable improvement in model selection, agent reliability, cost/latency, or task-success rate, not research for its own sake.
Build and lead the team
- Grow the Applied Research team, hiring and mentoring research scientists and engineers.
- Establish the team's operating rhythm: how research questions get scoped, how experiments get run and evaluated, and how findings hand off to production teams.
- Represent Applied Research in cross-functional planning cycles alongside other engineering and product leaders, and make the case for headcount and investment on its own merits.
Bridge research and product
- Partner directly with Inference Engine and the other platform and product engineering teams that own agent runtime and evaluation infrastructure to turn research into shipped capability.
- Turn research prototypes into production-ready capabilities in partnership with engineering — shipping research, not just publishing it.
- Communicate research trade-offs clearly to non-research stakeholders, including when a promising direction isn't ready for product investment yet.
Represent DigitalOcean externally
- Build DigitalOcean's credibility in the applied agentic-AI research community through publications, talks, open-source contributions, or collaborations — where they serve product and hiring goals.
What You'll Add to DigitalOcean
- 10+ years in applied ML/AI research or research-adjacent engineering, including experience leading a research team or function — formal people management or clear de facto technical leadership of a research group.
- Deep, hands-on expertise in at least two of: LLM routing and model selection, retrieval and memory systems, agent observability and evaluation, or reinforcement learning (RLHF, RLAIF, DPO, PPO, GRPO, or related methods).
- A track record of shipping research into production systems — not just publishing or prototyping it.
- Fluency with the current agentic AI landscape: reasoning, planning, tool use, long-horizon memory, and the practical economics of large-scale model serving.
- Strong technical communication — able to defend a research agenda to engineering leaders, product leaders, and executives, and to translate ambiguous research questions into a roadmap with concrete checkpoints.
Preferred Qualifications
Strong signal
- Experience building or scaling an applied research team inside a product organization (not a pure research lab), with research investment justified in business terms.
- Direct experience with inference infrastructure or large-scale model-serving optimization.
- Familiarity with the broader open-weight and open-source model ecosystem.
Nice to have
- PhD in CS, ML, or a related field — or equivalent depth demonstrated through industry impact.
- Publications, patents, or open-source contributions in routing, memory, agent evaluation, or reinforcement learning.
- Experience with small, specialized models or domain-tuned LLMs.
Compensation Range:
- $249,600 - $312,000
- This is a hybrid role
JR: 2026-8125
#LI-Hybrid
Why You'll Like Working for DigitalOcean
- We innovate with purpose. You'll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.
- We prioritize career development. At DO, you'll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.
- We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.
- We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.
- DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.
Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you'll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world.
DigitalOcean is building the Agentic Inference Cloud — anchored by Inference Engine, our model-serving platform — to help fast-growing AI-native companies start, scale, and optimize agentic workloads. Applied Research is the layer that generates the proprietary science that compounds across that platform: routing that learns instead of following static rules, memory that improves recall and personalization, observability that explains why agents succeed or get stuck, and reinforcement learning that closes the loop between production signals and model behavior.
We're hiring a Director of Research to build and lead this function: set the research agenda, grow the team, and make sure the science this group produces ships into real product outcomes — better model selection and routing, more reliable agents, lower cost and latency, and higher task-success rates for the developers and enterprises running agentic workloads on DigitalOcean.
This is a hybrid role by design: enough technical depth to personally evaluate and shape research direction across routing, memory, observability, and RL, and enough leadership range to build a team, prioritize against a roadmap, and defend research investment to product and executive stakeholders.
What You'll Do
Set the research agenda
- Define and own the applied research roadmap across adaptive routing (evolving model selection from static rules into a system that learns from real usage, cost, and latency), memory (retrieval quality and durable recall for long-running agents), agent observability (understanding when agents make progress, get stuck, or make mistakes), and reinforcement learning / closed-loop learning (turning production feedback into better models and policies).
- Track emerging model architectures and specialized, domain-tuned model approaches, and translate what's relevant into DigitalOcean's product roadmap.
- Keep the agenda tightly coupled to product outcomes — every research bet should map to a measurable improvement in model selection, agent reliability, cost/latency, or task-success rate, not research for its own sake.
Build and lead the team
- Grow the Applied Research team, hiring and mentoring research scientists and engineers.
- Establish the team's operating rhythm: how research questions get scoped, how experiments get run and evaluated, and how findings hand off to production teams.
- Represent Applied Research in cross-functional planning cycles alongside other engineering and product leaders, and make the case for headcount and investment on its own merits.
Bridge research and product
- Partner directly with Inference Engine and the other platform and product engineering teams that own agent runtime and evaluation infrastructure to turn research into shipped capability.
- Turn research prototypes into production-ready capabilities in partnership with engineering — shipping research, not just publishing it.
- Communicate research trade-offs clearly to non-research stakeholders, including when a promising direction isn't ready for product investment yet.
Represent DigitalOcean externally
- Build DigitalOcean's credibility in the applied agentic-AI research community through publications, talks, open-source contributions, or collaborations — where they serve product and hiring goals.
What You'll Add to DigitalOcean
- 10+ years in applied ML/AI research or research-adjacent engineering, including experience leading a research team or function — formal people management or clear de facto technical leadership of a research group.
- Deep, hands-on expertise in at least two of: LLM routing and model selection, retrieval and memory systems, agent observability and evaluation, or reinforcement learning (RLHF, RLAIF, DPO, PPO, GRPO, or related methods).
- A track record of shipping research into production systems — not just publishing or prototyping it.
- Fluency with the current agentic AI landscape: reasoning, planning, tool use, long-horizon memory, and the practical economics of large-scale model serving.
- Strong technical communication — able to defend a research agenda to engineering leaders, product leaders, and executives, and to translate ambiguous research questions into a roadmap with concrete checkpoints.
Preferred Qualifications
Strong signal
- Experience building or scaling an applied research team inside a product organization (not a pure research lab), with research investment justified in business terms.
- Direct experience with inference infrastructure or large-scale model-serving optimization.
- Familiarity with the broader open-weight and open-source model ecosystem.
Nice to have
- PhD in CS, ML, or a related field — or equivalent depth demonstrated through industry impact.
- Publications, patents, or open-source contributions in routing, memory, agent evaluation, or reinforcement learning.
- Experience with small, specialized models or domain-tuned LLMs.
Compensation Range:
- $249,600 - $312,000
- This is a hybrid role
JR: 2026-8125
#LI-Hybrid
Why You'll Like Working for DigitalOcean
- We innovate with purpose. You'll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.
- We prioritize career development. At DO, you'll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.
- We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.
- We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.
- DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.
See All 33 AI Researcher Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find AI Researcher JobsAI Researcher Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
AI Researcher Job Market in Washington
A snapshot from current Washington openings, updated as new roles post.
Who's Hiring
- ByteDance12
- TikTok4
- Meta3
- Apple3
- Google2
Top Industries Hiring
- Technology & Software
- Electronics & Hardware
- Social Media
- Science & Research
- Biotechnology & Pharmaceuticals
What Washington Employers Look For
The qualifications that appear most often in AI researcher jobs across Washington.
- PhD or master's degree in computer science, machine learning, or a closely related field
- Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow
- Published research or demonstrated contributions to peer-reviewed conferences like NeurIPS or ICML
- Strong proficiency in Python and familiarity with large-scale distributed computing environments
- Experience designing and running rigorous experiments, with clear documentation and reproducibility
- Ability to collaborate across engineering, product, and applied science teams on research projects
AI Researcher Jobs in Washington: Frequently Asked Questions
How do you become a ai researcher in Washington?
Most ai researchers working in Washington hold at least a master's degree, and the majority of research-track roles at Washington employers require a PhD in computer science, statistics, or a related field. Washington has no state-issued license or registration for this role. The practical path is completing an advanced degree with a thesis focus in machine learning or AI, building a publication record or strong project portfolio, and applying directly to research teams at Washington's large technology employers or university-affiliated labs such as the Allen Institute for AI.
How much do AI researchers make in Washington?
AI researchers in Washington earn a median of about $202,400 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $95,890 for the lowest 10% to over $281,050 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai researchers in Washington?
Employers hiring ai researchers in Washington right now include ByteDance, TikTok, and Meta, based on current listings on Migrate Mate as of September 2026. Washington's concentration of large technology headquarters and well-funded research labs makes it one of the few U.S. markets where dedicated research roles, rather than applied engineering positions, are posted consistently throughout the year.
Which Washington cities have the most ai researcher jobs?
Seattle, Redmond, and Bellevue have the most ai researcher openings in Washington. Seattle and Redmond together account for most of this volume because Microsoft and Amazon both maintain substantial core research organizations there, while Bellevue has grown as a secondary hub as those companies and mid-size AI-focused firms have expanded their footprints across the Eastside.
Are there remote ai researcher jobs in Washington?
Yes, and more than most fields. About 17% of ai researcher openings tied to Washington are remote or hybrid as of September 2026, reflecting the desk-based, compute-driven nature of most research work. The roles most likely to be fully remote are those focused on theoretical work, paper writing, and model evaluation, while positions that require close collaboration with hardware teams or access to proprietary compute clusters are more likely to require on-site presence.
How can I get hired as a ai researcher in Washington with little or no experience?
The most realistic entry path is a research internship at one of Washington's large technology employers during a graduate program, since Microsoft Research, Amazon Science, and the Allen Institute for AI all run structured internship pipelines that frequently convert to full-time offers. Candidates without a completed graduate degree can also target research engineer or machine learning engineer roles as a lateral entry point, then transition toward research responsibilities once inside. A strong GitHub portfolio with reproducible experiments, or a co-authored paper even from a workshop venue, gives Washington employers concrete evidence of research capability.
Where can I find and apply to ai researcher jobs in Washington?
You can find and apply to ai researcher jobs in Washington on Migrate Mate, which lists current Washington openings. Search the available roles, find the ones that fit your background and target location, and apply directly to each position.
See All 33 AI Researcher Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find AI Researcher Jobs