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Research Machine Learning Federated Learning Jobs in Seattle, WA

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AI Engineer - Machine Learning 3

Redmond, WA · Remote

$117K - $140K/yr

Machine Learning Data Scientist - Research Translation & Prototypin Top 3 Must-Have HARD Skills & years of experience for each:  1. Machine Learning & Applied AI Development (5-7 years) 2. Data ...

Factspan Inc

Machine Learning Engineer

Seattle, WA · On-site

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 ...

Adobe

Machine Learning Engineer

Seattle, WA

$93K - $125K/yr

We are looking for a Machine Learning Engineer to join our team of driven machine learning and ... Stay up to date with advancements in ML, GenAI, and prompt optimization research. * Mentor junior ...

PitchBook Data

Machine Learning Engineer

Seattle, WA · On-site

As a Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role ... Translate research findings into practical solutions that enhance PitchBook's AI capabilities

Qualtrics

Senior Machine Learning Engineer

Seattle, WA

$139K - $183K/yr

Senior Machine Learning Engineer Why We Have This Role We are looking for an engineer to bring our Machine Learning and Artificial Intelligence R&D strategy to the next level. Our goal is to ...

Qualtrics

Senior Machine Learning Engineer

Seattle, WA · On-site

$139K - $183K/yr

Senior Machine Learning Engineer Why We Have This Role We are looking for an engineer to bring our Machine Learning and Artificial Intelligence R&D strategy to the next level. Our goal is to ...

Bespoke Labs

Machine Learning Engineer

Bellevue, WA · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

AvePoint

Lead Machine Learning Engineer

Seattle, WA · On-site

$200K - $245K/yr

We are seeking an analytical and innovative Machine Learning Engineer to join our Data & AI team ... Collaborate cross-functionally with engineers, researchers, and product teams to define ...

Bespoke Labs

Machine Learning Engineer

Bellevue, WA

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Apple Inc.

AIML - Machine Learning Engineer, MIND

Seattle, WA · On-site

$139.50 - $258.10/hr

... research community. The team is well positioned for strategic contributions in the short-term (on ... Review and implement pioneering machine learning algorithms * Build software that improves rate of ...

Bespoke Labs

Machine Learning Engineer

Tacoma, WA

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

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Showing results 41-60

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 8, 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 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 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 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.

Senior / Staff Machine Learning Research Scientist, Agents

Scale AI

Seattle, WA • On-site

Full-time

Re-posted 29 days ago

Scale AI rating

8.5

Company rating: 8.5 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

78th of 242 rated software companies

Job description

Job Summary:
Scale AI is a leading AI data foundry focused on accelerating the development of AI applications. The Senior / Staff Machine Learning Research Scientist will conduct research on agent environments and reinforcement learning, guiding data strategy to innovate intelligent AI agents and contribute to impactful research publications.
Responsibilities:
• Explore the data landscape needed to advance intelligent, adaptable AI agents.
• Guide the data strategy at Scale to drive innovation.
• Contribute to impactful research publications on agents.
• Collaborate with customer researchers and work alongside the engineering team to translate advancements into real-world, scalable solutions.
Qualifications:
Required:
• Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow.
• A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)
• At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
• Strong written and verbal communication skills and the ability to operate cross-functionally.
Preferred:
• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax.
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH.
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.
Company:
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Founded in 2016, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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