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

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 ...

You will build and guide a high-performing team of data scientists and machine learning engineers ... Remote positions: Alaska, Delaware, Hawaii, Mississippi, Nebraska, Montana, New Hampshire, West ...

You will build and guide a high-performing team of data scientists and machine learning engineers ... Remote positions: Alaska, Delaware, Hawaii, Mississippi, Nebraska, Montana, New Hampshire, West ...

We use machine learning and real-world data to develop cybersecurity, device intelligence, network ... This position is fully remote. We are hiring across the US, UK, and Canada. In This Role, You Will

We use machine learning and real-world data to develop cybersecurity, device intelligence , network ... This position is fully remote. We are hiring across the US, UK, and Canada. In This Role, You Will:

Remote/Hybrid Relativity is a leading legal data intelligence company building technology that ... Select the appropriate modeling approach for each problem, ranging from classical machine learning ...

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Remote Machine Learning information

See Redmond, WA salary details

$28.6K

$47.7K

$98.6K

How much do remote machine learning jobs pay per year?

As of Jul 13, 2026, the average yearly pay for remote machine learning in Redmond, WA is $47,691.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,400.00 and $51,500.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Engineer, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

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.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
What are the most commonly searched types of Machine Learning jobs in Redmond, WA? The most popular types of Machine Learning jobs in Redmond, WA are:
What cities near Redmond, WA are hiring for Remote Machine Learning jobs? Cities near Redmond, WA with the most Remote Machine Learning job openings:
Infographic showing various Remote Machine Learning job openings in Redmond, WA as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $47,691 per year, or $22.9 per hour.
Staff Research Scientist (AdTech/Recommendation Systems)

Staff Research Scientist (AdTech/Recommendation Systems)

Cognitiv

Bellevue, WA • On-site, Remote

$200K - $270K/yr

Other

Posted 20 days ago


Job description

The Role

We are seeking a Staff Research Scientist who can drive innovation through deep technical expertise and hands-on execution. You'll contribute to cutting-edge research in deep learning and LLMs while advancing Cognitiv's real-time bidding and recommendation systems at production scale. This role sits at the intersection of applied research and high-performance machine learning systems.

Location: This position will be located in Bellevue, WA office with a hybrid work schedule of 3 days in office (Mon/Tue/Wed) and 2 days remote (Thursday/Friday).

What You'll Do
  • Drive Research & Innovation. Design, prototype, and evaluate advanced machine learning and deep learning approaches, with a focus on recommendation systems, real-time bidding, and LLM-driven applications.
  • Stay Hands-On. Contribute directly through coding, experimentation, model development, and technical problem-solving across the full ML lifecycle.
  • Advance AdTech Performance. Improve model accuracy, scalability, and efficiency to drive ad targeting, bidding performance, and audience relevance.
  • Build Production-Ready ML Systems. Partner closely with engineering and infrastructure teams to deploy, optimize, and monitor machine learning models in large-scale production environments.
  • Explore Emerging Technologies. Stay current with advancements in deep learning, transformers, and LLM research, identifying practical opportunities to apply new techniques within Cognitiv's platform.
  • Collaborate Cross-Functionally. Work closely with data science, engineering, product, and platform teams to solve complex technical challenges and deliver impactful ML solutions.
  • Contribute Technical Expertise. Provide thoughtful technical input through design discussions, experimentation reviews, and collaboration with other researchers and engineers.
Tech Stack
  • Core Tools - Python, PyTorch, deep learning architectures (transformers, recommendation models).
  • Traditional ML - XGBoost, PCA.
  • Big Data / Infra - Spark, Hadoop, distributed training systems.
  • Cloud Platforms - AWS, GCP, or Azure.
  • Bonus - C++.
Who You Are
  • Experienced ML Researcher/Engineer: Master's or Ph.D. in Computer Science, Statistics, Electrical Engineering, or a related field, with 5-7+ years of experience in machine learning R&D or applied ML.
  • Deep Learning & LLM Expertise: Strong technical expertise in PyTorch, transformers, and Large Language Models (LLMs), including large-scale training, fine-tuning, and optimization of deep neural networks.
  • Machine Learning Breadth: Strong understanding of both deep learning and traditional ML techniques (e.g., XGBoost, PCA), with the ability to apply the right approach to the right problem.
  • Engineering Excellence: Proficiency in Python with strong foundations in algorithms, data structures, and software engineering principles; experience building models in real-time, high-throughput systems (e.g., recommender systems, adtech).
  • Production Experience: Hands-on experience developing, deploying, and optimizing machine learning models in production environments, including distributed systems, cloud platforms (AWS, GCP, Azure), and big data frameworks (Hadoop, Spark).
  • Collaborative Communicator: Strong written and verbal communication skills with the ability to work effectively across research and engineering teams in a fast-paced environment.
Bonus Points If You Have
  • AdTech & RTB Experience. Prior exposure to advertising technology and real-time bidding (RTB) systems is a strong plus.
  • Distributed Systems & Cloud. Familiarity with big data frameworks (Spark, Hadoop) and cloud platforms (AWS, GCP, Azure).
  • C++ Skills. Strong C++ programming ability is a significant advantage alongside Python expertise.
  • Research & Community Impact. A track record of published research or meaningful contributions to the machine learning community.
  • Bridging Research and Production. Experience translating research ideas into scalable, production-grade machine learning systems.

Salary: $200,000 - $270,000 USD Base Salary + Equity