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Research Machine Learning Federated Learning Jobs in Bothell, WA

Apple

AIML - Machine Learning Research

Seattle, WA

$139.50K - $258.10K/yr

As part of this group, you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data ...

Hive

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine learning team. We are looking for an exceptional leader to help us with that growth, making sure that ...

Hive

Machine Learning Manager

Seattle, WA

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine learning team. We are looking for an exceptional leader to help us with that growth, making sure that ...

Sonsoft Inc

C# / Machine Learning

Redmond, WA

Machine Learning, Deep Learning/neural networks. * Data mining. * Azure ML, Cortana Intelligence. * Azure Data Lake. * Cosmos. * Analytical skills. * Experience and desire to work in a Global ...

Hive

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ... You are up-to-date on the latest deep neural net research and architectures, both in understanding ...

Hive

Machine Learning Engineer

Seattle, WA

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ... You are up-to-date on the latest deep neural net research and architectures, both in understanding ...

LVT

Machine Learning Engineer

Seattle, WA · On-site

$150.50K - $208K/yr

Explore and research new and emerging ML technologies for the company * Share insight into which types of problems are most appropriate for machine learning * Provide guidance on distributed training ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Research and implement appropriate ML algorithms and tools * Develop machine learning applications according to requirements * Select appropriate datasets and data representation methods * Run ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Research and implement appropriate ML algorithms and tools * Develop machine learning applications according to requirements * Select appropriate datasets and data representation methods * Run ...

PitchBook

Machine Learning Engineer

Seattle, WA · On-site

Translate research findings into practical solutions that enhance PitchBook's AI capabilities • ... machine learning engineering, with a strong focus on AI/ML applications in insight generation ...

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All JobsResearch Machine Learning Federated Learning JobsResearch Machine Learning Federated Learning Jobs in Bothell, WA

Research Machine Learning Federated Learning information

See Bothell, WA salary details

$28.5K

$47.6K

$98.4K

How much do research machine learning federated learning jobs pay per year?

As of May 29, 2026, the average yearly pay for research machine learning federated learning in Bothell, WA is $47,604.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,300.00 and $51,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Researcher in Machine Learning Federated Learning, and why are they important?

To thrive as a Researcher in Machine Learning Federated Learning, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant advanced degree (e.g., PhD or MSc). Familiarity with Python, TensorFlow, PyTorch, and distributed computing frameworks, as well as knowledge of privacy-preserving techniques and relevant research publications, is essential. Excellent analytical thinking, problem-solving abilities, and clear scientific communication are key soft skills for success in collaborative research environments. These competencies are vital to drive innovation, rigorously evaluate federated learning approaches, and advance privacy-preserving AI technologies.

What are some common challenges faced when implementing federated learning in a research environment?

One of the primary challenges in research-focused federated learning roles is ensuring data privacy and security while maintaining model performance across distributed devices. Researchers must also address issues such as handling heterogeneous data sources, communication bottlenecks between nodes, and the complexity of debugging decentralized systems. Collaborating with cross-functional teams—such as data engineers, privacy experts, and domain specialists—is vital to overcome these hurdles and drive successful outcomes. Staying updated with the latest advancements and actively contributing to open-source initiatives can also help researchers address these evolving challenges.

What is a Researcher in Machine Learning Federated Learning?

A Researcher in Machine Learning Federated Learning is a professional who investigates and develops methods to train machine learning models across multiple decentralized devices or servers, while keeping data localized and private. Their work focuses on improving algorithms, ensuring data privacy, and addressing challenges related to distributed learning, communication efficiency, and model accuracy. They often collaborate with other researchers, publish findings, and contribute to advancing technologies that make it possible to use sensitive data for AI without compromising privacy.

What is the difference between Research Machine Learning Federated Learning vs Data Scientist?

AspectResearch Machine Learning Federated LearningData Scientist
CredentialsAdvanced degrees in CS, ML, or related fields; research experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, academic institutions, tech companies focusing on privacy-preserving MLBusiness environments, analytics teams, data-driven departments
Industry UsageDeveloping federated algorithms, privacy-preserving ML modelsData analysis, modeling, reporting, and insights generation

Research Machine Learning Federated Learning specialists focus on developing privacy-preserving algorithms across distributed data sources, often in research or R&D settings. Data Scientists analyze and interpret data to inform business decisions. While both roles require strong ML knowledge, federated learning roles emphasize distributed systems and privacy, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Research Machine Learning Federated Learning jobs in Bothell, WA? For Research Machine Learning Federated Learning jobs in Bothell, WA, the most frequently searched job titles are:
What cities near Bothell, WA are hiring for Research Machine Learning Federated Learning jobs? Cities near Bothell, WA with the most Research Machine Learning Federated Learning job openings:
Research Machine Learning Federated Learning jobs near you
Infographic showing various Research Machine Learning Federated Learning job openings in Bothell, WA as of May 2026, with employment types broken down into 19% Internship, 68% Full Time, and 13% Part Time. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $47,604 per year, or $22.9 per hour.

Research Scientist - AI Incubation

Zoom Video Communications, Inc.

Seattle, WA • On-site

$137.70K - $275.40K/yr

Full-time

Posted 24 days ago

Job description

What you can expect
Zoom's AI Incubation team is seeking a Research Scientist to contribute to the next wave of LLM post-training, reinforcement learning, and federated AI innovation. You will join a world-class group of PhDs and applied scientists focused on pushing the boundaries of model alignment, reasoning, and agentic intelligence.
As a Research Scientist, you will advance Zoom's applied AI research, working with cutting-edge LLM post-training, RLHF/DPO/RLAIF, federated AI, and multimodal intelligence to deliver breakthroughs that redefine human-AI collaboration. You will participate in incubation efforts that transform bold research ideas into scalable, production-ready systems powering the next generation of Zoom AI Companion.
About the Team
The AI Incubation team is a high-impact applied research group that has built one of the best-performing federated AI systems in the industry. The team operates at the frontier of LLM post-training, reinforcement learning for agentic AI, multimodal understanding, federated AI, and AI evaluation.
Zoom's federated AI architecture-spanning Anthropic, OpenAI, and Google models-enables privacy-preserving, edge-to-cloud learning that adapts to user context while maintaining enterprise-grade governance. The Incubation team plays a central role in advancing this federated AI leadership, developing new methods for distributed model optimization, personalized prefix learning, and secure collaboration.
Responsibilities
  • Conducting frontier research in LLM post-training, reinforcement learning, and federated AI to achieve state-of-the-art reasoning, personalization, and reliability.
  • Developing and implementing evaluation and benchmarking frameworks for model performance, safety, and user experience across distributed environments.
  • Contributing to model architectures, fine-tuning strategies, and reinforcement learning pipelines across Zoom's federated AI ecosystem.
  • Partnering with product and infra teams to translate research prototypes into scalable, production-grade AI systems that leverage edge and cloud collaboration.
  • Participating in a culture of scientific rigor, creativity, and rapid experimentation.
  • Exploring emerging AI paradigms-from agentic reasoning and multimodal fusion to self-improving federated systems-to continuously advance Zoom's AI frontier.

What we're looking for
  • Have a PhD or advanced degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
  • Demonstrate proven expertise in LLM post-training, RLHF/DPO/PPO, federated learning, or reinforcement learning for reasoning and alignment.
  • Have deep understanding of large-scale distributed training systems and experience with PyTorch, Transformers, DeepSpeed, or CUDA.
  • Hold a publication or open-source record demonstrating innovation in LLM optimization, federated AI, or agentic intelligence.
  • Demonstrate passion for applied AI research that bridges scientific discovery and real-world impact.
  • Have experience implementing AI research concepts and translating them into practical applications.

Salary Range or On Target Earnings:
Minimum:
$137,700.00
Maximum:
$275,400.00
In addition to the base salary and/or OTE listed Zoom has a Total Direct Compensation philosophy that takes into consideration; base salary, bonus and equity value.
Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience.
We also have a location based compensation structure; there may be a different range for candidates in this and other locations.
Ways of Working
Our structured hybrid approach is centered around our offices and remote work environments. The work style of each role, Hybrid, Remote, or In-Person is indicated in the job description/posting.
Benefits
As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways. Click Learn for more information.
About Us
Zoomies help people stay connected so they can get more done together. We set out to build the best collaboration platform for the enterprise, and today help people communicate better with products like Zoom Contact Center, Zoom Phone, Zoom Events, Zoom Apps, Zoom Rooms, and Zoom Webinars.
We're problem-solvers, working at a fast pace to design solutions with our customers and users in mind. Find room to grow with opportunities to stretch your skills and advance your career in a collaborative, growth-focused environment.
Our Commitment
At Zoom, we believe great work happens when people feel supported and empowered. We're committed to fair hiring practices that ensure every candidate is evaluated based on skills, experience, and potential. If you require an accommodation during the hiring process, let us know-we're here to support you at every step.
We welcome people of different backgrounds, experiences, abilities and perspectives including qualified applicants with arrest and conviction records and any qualified applicants requiring reasonable accommodations in accordance with the law.
If you need assistance navigating the interview process due to a medical disability, please submit an Accommodations Request Form and someone from our team will reach out soon. This form is solely for applicants who require an accommodation due to a qualifying medical disability. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed.
Think of this opportunity as a marathon, not a sprint! We're building a strong team at Zoom, and we're looking for talented individuals to join us for the long haul. No need to rush your application - take your time to ensure it's a good fit for your career goals. We continuously review applications, so submit yours whenever you're ready to take the next step.
Our interviews are supported by BrightHire, a tool that helps us create a consistent and thoughtful interview experience and may include recordings. Please refer to our candidate privacy statement for more information of how we use your data.

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