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Machine Learning Research Engineer Jobs in Seattle, WA

Apple

AIML - Machine Learning Research

Seattle, WA · On-site

$139K - $258K/yr

AIML - Machine Learning Research Apple is where individual imaginations gather together, committing ... Driving cross-functional technical initiatives, collaborating with research, engineering and ...

Apple

AIML - Machine Learning Research

Seattle, WA

$139K - $258K/yr

This involves developing sophisticated machine learning and large language models (LLMs) to ... Driving cross-functional technical initiatives, collaborating with research, engineering and ...

Cobot

AI Research Engineer

Seattle, WA · On-site

Are you passionate about advancing the state of artificial intelligence and machine learning? Our rapidly growing startup is seeking an AI Research Engineer to join our Foundational Models AI team.

RBC

Principal Machine Learning Researcher

Seattle, WA · On-site

$154K - $268K/yr

Advanced Machine Learning Research Lead Leads the strategic direction and execution of advanced ... Programming Languages Job Details: Address: 401 Union Street:Seattle City: Seattle Country: United ...

Apple

Machine Learning Engineer

Seattle, WA

$171K - $302K/yr

... Machine Learning Engineer with experience developing ML models for computer vision and graphics ... We perform applied research development to adapt state-of-the-art methods or implement new methods ...

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All JobsMachine Learning Research Engineer JobsMachine Learning Research Engineer Jobs in Seattle, WA

Machine Learning Research Engineer information

See Seattle, WA salary details

$42.1K

$120.6K

$162.2K

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

As of Jun 16, 2026, the average yearly pay for machine learning research engineer in Seattle, WA is $120,645.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,400.00 and $118,400.00 per year, depending on experience, location, and employer.

What does a Machine Learning Research Engineer do?

A Machine Learning Research Engineer develops and improves machine learning models, conducts research to advance AI techniques, and implements scalable algorithms. They work at the intersection of applied research and engineering, leveraging mathematical and statistical methods to optimize performance. Their role involves experimenting with new architectures, analyzing large datasets, and collaborating with data scientists and software engineers to deploy models into production.

What are some common challenges faced by Machine Learning Research Engineers in their daily work?

Machine Learning Research Engineers often encounter challenges such as sourcing and preparing large, high-quality datasets, tuning complex model architectures, and ensuring reproducibility of experimental results. They work closely with cross-functional teams, including data scientists and software engineers, to deploy models in production environments and must frequently adapt to rapidly evolving research. Keeping up with the latest scientific literature and integrating new algorithms into ongoing projects can be demanding but is also rewarding. This collaborative, fast-paced environment provides constant opportunities for learning and professional development.

What are the key skills and qualifications needed to thrive in the Machine Learning Research Engineer position, and why are they important?

A Machine Learning Research Engineer typically needs a strong background in computer science, mathematics, and statistics, often with a graduate degree in a related field. Proficiency in programming languages such as Python or C++, experience with machine learning frameworks like TensorFlow or PyTorch, and familiarity with tools for data analysis are crucial, along with relevant certifications being a plus. Strong problem-solving skills, collaboration, and effective communication help drive innovative research and facilitate teamwork. These competencies are essential for developing advanced machine learning models, staying current with evolving technologies, and effectively translating research into real-world applications.

What are popular job titles related to Machine Learning Research Engineer jobs in Seattle, WA? For Machine Learning Research Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Research Engineer jobs in Seattle, WA look for? The top searched job categories for Machine Learning Research Engineer jobs in Seattle, WA are:
Machine Learning Research Engineer jobs near you
Infographic showing various Machine Learning Research Engineer job openings in Seattle, WA as of June 2026, with employment types broken down into 8% Internship, and 92% Full Time. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $120,645 per year, or $58 per hour.
LLM Machine Learning Research Engineer

LLM Machine Learning Research Engineer

Apple

Seattle, WA

Other

Posted 4 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

Apple is seeking a Research Engineer to join our Foundation Model Preparation and Algorithm Team. We are looking for all levels of talent to bring innovative AI research into Apple products.
We are looking for strong ML applied scientists and engineers to build groundbreaking AI infrastructure and algorithms. This infrastructure will power the optimization of Apple Foundation models, including on-device and server Apple Intelligence models. My team is directly responsible for general model capability, use-case-oriented post-training, and also the feature delivery for Apple Intelligence.\n\nYou should be a strong scientist and/or engineer who has a background in building state-of-the-art LLMs. Your work will have a direct impact on billions of Apple clients. You will collaborate with world-class talent in LLM training, on-device and server optimization, ML tools/platforms, datasets, and evaluation. You will develop reliable and scalable pipelines and algorithms, such as:Model optimization pipelines, State-of-the-art optimization algorithms, State-of-the-art post-training techniques.
Experience developing, optimizing, or training large language models (LLMs), large foundation models, or generative AI models.\nSoftware engineering skills in Python and general-purpose system administration and infrastructure management abilities.\nHistory of applied research in the neural network model life cycle, training, or a related application area.\nExperience with languages like Python, C/C++.\nTrack record of driving scientific investigations and experiments, and overcoming obstacles and uncertainty in a research environment.\nBS degree and 3+ years of proven experience.
Publication record at top AI/ML venues.\nExperience with LLM LoRA fine-tuning, neural network optimization (e.g., quantization, palettization).\nExperience with LLM pre-training or post-training.\nExperience with on-device/server scale deployment.\nInfrastructure management and debugging experience.\nExperimental rigor when training/evaluating LLMs for the purpose of benchmarking LLM optimization algorithms.\nStrong communication and accountability skills; a hard-working, strong work ethic, and collaboration abilities.\nPh.D. in a related field.

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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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