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Remote Deep Learning Engineer Jobs in Auburn, WA

Deep Learning Quality Specialist

Seattle, WA ยท On-site +1

$72K - $90K/yr

Our office is based in Seattle, WA, but this role can be fully remote. What you'll do: * Audit data ... Help the Deep Learning team prioritize tasks based on impact to customer satisfaction Knowledge ...

Senior Machine Learning Engineer

Seattle, WA ยท On-site +1

$186K - $300K/yr

Develop and deploy deep learning models (Transformers, LSTMs, etc.) for forecasting and anomaly ... Employee divides their time between in-office and remote work. Access to an office location is ...

Machine Learning Engineer

Seattle, WA ยท On-site +1

$164K - $266K/yr

Employee divides their time between in-office and remote work. Access to an office location is ... Deep understanding of the ML lifecycle, from data ingestion and training to production monitoring

Senior Machine Learning Engineer

Bellevue, WA ยท On-site +1

$149K - $245K/yr

... Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ... Machine learning and deep-learning models will influence selection, relevance, ranking, click ...

Bellevue, WA Remote Work100% Primary SkillsAWS Cloud Formation * MLOps Engineer to work on AWS ... deep learning, NLP with Python in a programming intensive role. * 6-8 years of strong experience in ...

Machine Learning Engineer

Bellevue, WA ยท On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

Computer Vision Engineer

Seattle, WA ยท On-site +1

$160K - $275K/yr

Run experiments at scale with deep learning frameworks like PyTorch * Develop and maintain clean ... Experience with high-res aerial/remote sensing imagery and LiDAR * Experience with self-supervised ...

Senior Machine Learning Engineer II

Seattle, WA ยท On-site +1

$118K - $163K/yr

Your Impact We are seeking a seasoned Machine Learning Engineer to join a new team building agentic ... Deep experience building systems across the ML lifecycle: data pipelines, training and evaluation ...

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Remote Deep Learning Engineer information

See Auburn, WA salary details

$12K

$91.6K

$152.9K

How much do remote deep learning engineer jobs pay per year?

As of Jul 31, 2026, the average yearly pay for remote deep learning engineer in Auburn, WA is $91,645.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,700.00 and $151,900.00 per year, depending on experience, location, and employer.

How do Remote Deep Learning Engineers typically collaborate with cross-functional teams despite working remotely?

Remote Deep Learning Engineers frequently collaborate with data scientists, product managers, and software engineers using digital tools such as Slack, Zoom, and collaborative code platforms like GitHub. Regular virtual meetings and sprint planning sessions help ensure alignment on project goals and milestones. Clear documentation and asynchronous communication are crucial for effective teamwork, especially when team members are in different time zones. This collaborative structure enables remote engineers to contribute meaningfully to model development, deployment, and integration while maintaining flexibility.

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

To thrive as a Remote Deep Learning Engineer, you need a strong background in machine learning, deep learning frameworks, and programming languages like Python, usually supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (e.g., AWS, GCP), and version control systems is typically required, with certifications in AI or cloud technologies being advantageous. Excellent problem-solving, communication, and self-management skills make candidates stand out in remote environments. These skills and qualities are essential for developing effective AI solutions, collaborating across distributed teams, and driving innovation in the fast-evolving field of deep learning.

What is the difference between Remote Deep Learning Engineer vs Remote Machine Learning Engineer?

AspectRemote Deep Learning EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with deep learning frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch and development, model training, neural network designData analysis, model deployment, algorithm development
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, e-commerce

Remote Deep Learning Engineers focus on designing and training neural networks for complex AI tasks, while Remote Machine Learning Engineers work on broader ML models and algorithms. Both roles require strong programming skills and knowledge of machine learning frameworks, but Deep Learning Engineers specialize in neural networks and large-scale data processing.

What is a Remote Deep Learning Engineer?

A Remote Deep Learning Engineer is a professional who works primarily online to design, develop, and implement deep learning models and algorithms. These engineers use neural networks and large datasets to solve complex problems in fields like computer vision, natural language processing, and more. Working remotely, they collaborate with team members via digital tools, write code, optimize models, and often deploy solutions to cloud environments. This role requires strong programming skills, experience with deep learning frameworks (like TensorFlow or PyTorch), and the ability to work independently in a distributed team setting.
What job categories do people searching Remote Deep Learning Engineer jobs in Auburn, WA look for? The top searched job categories for Remote Deep Learning Engineer jobs in Auburn, WA are:

Deep Learning Quality Specialist

Carbon Robotics

Seattle, WA โ€ข On-site, Remote

Other

Re-posted 12 days ago


Job description

As a Deep Learning Quality Specialist at Carbon Robotics you'll be responsible for maintaining our expanding dataset of high resolution images that feed our computer vision algorithms. You will develop a deep understanding of our data annotation practices and assist in diagnosing & fixing complex deep learning models to ensure our products are robust & reliable. You will help the Deep Learning team by performing field tests and identifying issues with models. You'll do whatever it takes - which includes going to the farm - to ensure our customers have reliable and safe products.

Our office is based in Seattle, WA, but this role can be fully remote.ย 

What you'll do:

  • Audit data to ensure clean and appropriate datasets
  • Look through imagery and correct labels and classifications then give feedback to labelers
  • Work closely with support to help investigate issues and determine what is needed to insure data integrity
  • Review data irregularities detected by automated tooling
  • Validate solutions, document results and record customer feedback
  • Translates field tests, model issues and analyze customer feedback
  • Prepare cases for field personnel to review labels/predictions
  • Help the Deep Learning team prioritize tasks based on impact to customer satisfaction

Knowledge, Skills, and Abilities for Success:

  • Education or professional experience in agronomy & farming or data annotation
  • Highly motivated, independent thinker with great problem solving skills
  • Highly organized with excellent time management to juggle multiple priorities at the same time
  • Collaboration skills to work with customers and internal teams simultaneously
  • High level of attention to detail & the ability to think strategically
  • Detail-oriented, with proven ability to deliver accurate reporting
  • Intermediate to advanced Google Suite and Confluence skills desired
  • Ability to assess high risk situations & make safe independent decisions on a risk based process
  • Traveling required 10-15%