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Remote Deep Learning Jobs (NOW HIRING)

Carbon Robotics

Deep Learning Quality Specialist

Seattle, WA · 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 ...

Carbon Robotics

Deep Learning Quality Specialist

Seattle, WA · 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 ...

NBCUniversal

Senior Deep Learning Engineer

$107K - $146K/yr

They are seeking a Senior Deep Learning Engineer to implement core algorithms at the intersection ... remote machines via a Unix shell to deploy and test code on large-scale geospatial datasets ...

NBCUniversal

Staff Deep Learning Engineer

They are seeking a Deep Learning Engineer to implement core algorithms at the intersection of ... remote machines via a Unix shell to deploy and test code on large-scale geospatial datasets ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Build andoptimizepredictive and generative models (e.g., deep learning, probabilistic models ...

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How much do remote deep learning jobs pay per year?

As of Jul 10, 2026, the average yearly pay for remote deep learning in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is a Remote Deep Learning job?

A Remote Deep Learning job involves working with artificial intelligence and machine learning models, particularly using deep neural networks, from a location outside a traditional office, often from home. Professionals in this field design, build, and optimize algorithms that enable computers to learn from large amounts of data. They often work on projects such as image and speech recognition, natural language processing, or autonomous systems. The remote aspect allows flexibility and access to global opportunities, but requires strong communication skills and the ability to collaborate virtually with teams.

What are some common challenges faced by remote deep learning engineers, and how can they be addressed?

Remote deep learning engineers often encounter challenges such as limited access to high-performance computing resources, communication barriers with distributed teams, and difficulties in collaborating on large codebases or datasets. These issues can be mitigated by leveraging cloud-based platforms for scalable computing, using clear communication tools like Slack or Zoom for regular check-ins, and employing version control systems like Git for collaborative code management. Proactively setting up workflows and documentation helps ensure smooth collaboration and project continuity within a remote environment.

How can I make $100,000 a year working from home?

A remote deep learning professional can reach a $100,000 annual income by gaining advanced skills in machine learning frameworks, building a strong portfolio, and working for companies that offer competitive salaries or freelance projects. Earning this level often requires experience, specialized knowledge, and the ability to deliver high-quality models efficiently. Certifications in deep learning and proficiency with tools like Python, TensorFlow, or PyTorch can also enhance earning potential.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data science, and programming. These roles usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses as part of compensation packages.

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

AspectRemote Deep LearningRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with neural networksBachelor's/Master's in CS, Data Science, or related; experience with algorithms and data modeling
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesDevelopment teams, data-driven projects, across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech companies, finance, healthcare, e-commerce

Remote Deep Learning specialists focus on designing and training neural networks for AI applications, often requiring advanced knowledge of deep neural architectures. Remote Machine Learning Engineers work on developing algorithms and models for broader data analysis and predictive tasks. While both roles involve machine learning, deep learning emphasizes neural networks, whereas machine learning engineers may work with a variety of algorithms across industries.

Which 3 jobs will survive AI?

In the field of remote deep learning, roles such as data scientists, machine learning engineers, and AI research scientists are likely to persist due to their reliance on complex problem-solving, domain expertise, and ongoing innovation. These jobs require advanced skills in programming, mathematics, and understanding of AI frameworks, making them less susceptible to automation by AI systems. Continuous learning and staying updated with new tools and techniques are essential for long-term career stability in this area.

How to make $1000 a week remotely?

Remote deep learning professionals can earn $1000 or more weekly by taking on freelance projects, consulting, or working for companies that pay competitive rates. Building a strong portfolio, acquiring relevant skills in Python and machine learning frameworks, and obtaining certifications can help increase earning potential. Consistent work and specialized expertise are key to reaching this income level remotely.

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 strong programming skills in Python, a deep understanding of machine learning algorithms, and typically a degree in computer science, engineering, or a related field. Proficiency with frameworks like TensorFlow or PyTorch, as well as cloud computing platforms such as AWS or Google Cloud, is essential, and certifications in these technologies can be advantageous. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These skills ensure effective development, deployment, and maintenance of deep learning models while working independently in distributed teams.
More about Remote Deep Learning jobs
What cities are hiring for Remote Deep Learning jobs? Cities with the most Remote Deep Learning job openings:
What are the most commonly searched types of Deep Learning jobs? The most popular types of Deep Learning jobs are:
What states have the most Remote Deep Learning jobs? States with the most job openings for Remote Deep Learning jobs include:
What job categories do people searching Remote Deep Learning jobs look for? The top searched job categories for Remote Deep Learning jobs are:
Remote Deep Learning jobs near you
Infographic showing various Remote Deep Learning job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 25% Part Time, and 2% Contract. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution, with an average salary of $83,885 per year, or $40.3 per hour.
Deep Learning Quality Specialist

Deep Learning Quality Specialist

Carbon Robotics

Seattle, WA • On-site, Remote

Other

Posted 20 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. 

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%

Apply