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Research Machine Learning Federated Learning Jobs in Seattle, WA

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 · 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 ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Responsibilities : • Study and transform data science prototypes • Design machine learning systems • Research and implement appropriate ML algorithms and tools • Develop machine learning ...

Apple

Machine Learning Engineer

Seattle, WA

$175K - $308K/yr

We perform applied research development to adapt state-of-the-art methods or implement new methods ... machine learning or related field PhD in computer vision, computer graphics, machine learning ...

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 ...

Factspan Inc

Machine Learning Engineer

Seattle, WA

Hands on expertise in Machine Learning models using R/Python, SQL, well versed in statistical methodology including deep expertise and experience with statistical data analysi * Requires a ...

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

Research Machine Learning Federated Learning information

See Seattle, WA salary details

$29K

$48.5K

$100.1K

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

As of Aug 23, 2026, the average yearly pay for research machine learning federated learning in Seattle, WA is $48,461.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,000.00 and $52,300.00 per year, depending on experience, location, and employer.

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 are the key skills and qualifications needed to thrive as a researcher in machine learning federated learning?

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 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 Seattle, WA?

For Research Machine Learning Federated Learning jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Research Machine Learning Federated Learning jobs in Seattle, WA look for?

The top searched job categories for Research Machine Learning Federated Learning jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Research Machine Learning Federated Learning jobs?

Cities near Seattle, 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 Seattle, WA as of August 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $48,461 per year, or $23.3 per hour.

Machine Learning Research Scientist - Health AIML

Apple Inc.

Seattle, WA • On-site

$205.40 - $374.30/hr

Other

Medical, Dental, Retirement

Re-posted 21 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

Machine Learning Research Scientist - Health AIML

Seattle, Washington, United States Machine Learning and AI

The Health AIML team is at the forefront of machine learning and health science at Apple. We are a close-knit team of research scientists, software engineers and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a Machine Learning Research Scientist with strong dedication to solving real-world problems in health and fitness that enrich our customers' lives.

Description

We’re developing next-generation multimodal models to create intelligent health and fitness experiences. This role requires someone with strong expertise in large multimodal models to work at the intersection of AI and health to build foundational models that scale to billions of users worldwide. Your work will shape the future of health and fitness technologies at Apple. We are looking for a research lead to guide multimodality research. You will lead the development of foundational technology that enables models to understand health and fitness data.

Responsibilities
  • Lead research into health and fitness representation models and multimodal models.
  • Design, prototype and scale up new architectures to improve model intelligence.
  • Execute and analyze experiments autonomously and collaboratively.
  • Study, debug, and optimize model performance and computational performance.
  • Contribute to training and inference infrastructure.
  • Guide technical and architectural decision.
Minimum Qualifications
  • PhD in Computer Science/Engineering, Machine Learning, Statistics, Mathematics or related field.
  • Industry work experience.
  • Experience landing contributions to major LLM training runs.
  • Proven track record of publishing SOTA.
  • Strong skills with deep learning frameworks such as PyTorch, JAX, or TensorFlow.
Preferred Qualifications
  • Experience in training and evaluating multimodal models.
  • Understand of time-series modeling, self-supervised learning, and cross-modal training.
  • Ability to thoroughly evaluate and improve deep learning architectures in a self-directed fashion.
  • Motivated by safely deploying LLMs in the health and fitness space.
Compensation and Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $205,400 and $374,300, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan.

You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Equal Opportunity Employment

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

Accessibility

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace.

Learn about reasonable accommodations for job applicants.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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