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Remote Machine Learning Jobs in Bellevue, WA (NOW HIRING)

Senior Machine Learning System Engineer

Seattle, WA ยท On-site +1

$139K - $183K/yr

About AI & ML Platform Team Our team's goal is to build the foundations to democratize AI and Machine Learning for Atlassian's teams, customers, and ecosystem. We aim to build productive and reliable ...

Machine Learning Data Engineer

Seattle, WA ยท Remote

$130K - $160K/yr

Build and improve the continuous learning pipeline so new models ship weekly with minimal manual engineering effort. * Define functional acceptance criteria for CV accuracy per customer and track ...

... remote Who We Need We are seeking a highly motivated and talented Machine Learning PhD Intern to join our AI research team and contribute to our innovative projects in the field of Large Language ...

Senior Software Engineer - Remote

Seattle, WA ยท Remote

$139K - $183K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Bellevue, WA Remote Work100% Primary SkillsAWS Cloud Formation * MLOps Engineer to work on AWS ... Overall, 8-10 years of solid experience in the areas of data engineering / machine learning / data ...

Showing results 21-40

Remote Machine Learning information

See Bellevue, WA salary details

$28.8K

$48.1K

$99.3K

How much do remote machine learning jobs pay per year?

As of Aug 18, 2026, the average yearly pay for remote machine learning in Bellevue, WA is $48,061.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,700.00 and $51,900.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

What are the most commonly searched types of Machine Learning jobs in Bellevue, WA?

The most popular types of Machine Learning jobs in Bellevue, WA are:

What are popular job titles related to Remote Machine Learning jobs in Bellevue, WA?

For Remote Machine Learning jobs in Bellevue, WA, the most frequently searched job titles are:

What cities near Bellevue, WA are hiring for Remote Machine Learning jobs?

Cities near Bellevue, WA with the most Remote Machine Learning job openings:

Infographic showing various Remote Machine Learning job openings in Bellevue, WA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $48,061 per year, or $23.1 per hour.

Senior Machine Learning System Engineer

Atlassian

Seattle, WA โ€ข On-site, Remote

$139K - $183K/yr

Other

Re-posted 5 days ago


Job description

Overview
Working at Atlassian
Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
Responsibilities
About Central AI Org
Our organization is dedicated to driving AI innovation across all Atlassian products and platforms. We aim to deliver seamless AI experiences while establishing a robust Atlassian AI infrastructure for the future. Our purpose is to:
  1. Develop horizontal AI capabilities and infrastructure that can be leveraged across all products.
  2. Establish a centralized Search, Q&A, and Conversational AI system that integrates seamlessly with all Atlassian products.
  3. Explore the integration of Atlassian products with AI solutions beyond the Atlassian ecosystem.
About AI & ML Platform Team
Our team's goal is to build the foundations to democratize AI and Machine Learning for Atlassian's teams, customers, and ecosystem. We aim to build productive and reliable tools that empower Atlassian teams to harness the power of AI. These tools will facilitate the development, deployment, measurement, and operation of AI & ML experiences.
Our tools are designed to integrate seamlessly with other Atlassian platforms, including the Atlassian Data Platform. This integration enables teams to efficiently and swiftly incorporate AI and ML capabilities into their workflows while strictly adhering to all security and data usage policies. Our primary goal is to deliver a smooth and hassle-free experience for Atlassian users, empowering them to harness the potential of AI and ML without any complications.
About This Role
As a Senior ML System Engineer on the AI & ML Platform team, you will play a pivotal role in developing and refining the core infrastructure that empowers all Atlassian software engineers, ML engineers, and data scientists to create, train, evaluate, deploy, and manage Machine Learning models and pipelines.
You will collaborate closely with product teams, such as Jira and Confluence, to solve their specific challenges in building ML solutions. This may involve curating high-quality ML datasets, fine-tuning open-sourced Large Language Models (LLMs), or accessing proprietary LLMs. Your expertise in both ML and software development expertise will be instrumental in overcoming challenging problems and navigating complex infrastructure and architectural issues.
This position offers you the chance to lead projects from the technical design phase all the way to launch. You will partner with various teams and internal stakeholders to achieve impactful results.
In this role, you'll get the chance to:
  • Collaborate with your teammates to solve complex problems, from technical design to launch.
  • Deliver cutting-edge solutions that are used by other Atlassian teams and products to build AI features that reach millions of customers.
  • Deliver code reviews, documentation & bug fixes within a strong engineering culture
  • Partner across engineering teams to take on company-wide initiatives spanning multiple projects.
  • Mentor junior members of the team.
On your first day, we'll expect you to have
  • 5+ years of experience in building Machine Learning and AI infra/platform/system
  • Comprehensive ML lifecycle expertise: proven experience developing, deploying, and maintaining end-to-end ML systems, from data engineering to model serving and monitoring.
  • Large-scale system design: Extensive experience designing and building scalable, fault-tolerant, and high-performance distributed systems for machine learning.
  • MLOps and automation: Deep experience implementing MLOps, CI/CD pipelines, and automation for continuous training, deployment, and monitoring of ML models.
It would be great, but not required if you have
  • Proficiency with frameworks and languages: Expert-level proficiency in Python and ML frameworks like PyTorch, TensorFlow, or JAX. Familiarity with other languages like Go, Java, or Scala is also beneficial.
  • Cloud infrastructure: Hands-on expertise with major cloud platforms such as AWS, GCP, or Azure, including their specific AI/ML services and compute resources like GPUs.
  • Big data processing: Experience with distributed computing frameworks for large-scale data processing, such as Spark, Ray, or Dask.
  • Performance optimization: A demonstrated ability to diagnose and solve complex performance and optimization problems for ML models and infrastructure.
  • Generative AI systems: Experience with GenAI frameworks and tools, including developing and fine-tuning large language models (LLMs) and building retrieval-augmented generation (RAG) systems.

Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
This role may also be eligible for benefits, bonuses, commissions, and equity.
Pay Ranges
In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $180,000 - $235,000
Zone B: $162,000 - $211,500
Zone C: $149,400 - $195,050
Qualifications
Benefits & Perks
Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.
We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.
To learn more about our culture and hiring process, visit go.atlassian.com/crh
In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.