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Remote Medical Data Encoder Jobs in California (NOW HIRING)

Catasys Health

Data Architect- REMOTE

Santa Monica, CA · On-site +1

$71.50 - $92/hr

... medical consequences of untreated behavioral health conditions. You will work in a highly ... You will be responsible for all phases of new data solution implementation displaying the ability ...

Catasys Health

Data Architect- REMOTE

Santa Monica, CA · Remote

$71.50 - $92/hr

... medical consequences of untreated behavioral health conditions. You will work in a highly ... You will be responsible for all phases of new data solution implementation displaying the ability ...

Eluvio

Senior Software Engineer - Video

Berkeley, CA · On-site +1

$150K - $197K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Our work extends the state-of-the-art in video engineering, Internet networking, data science ... In depth knowledge of media packaging and encoding (MP4/FMP4/CMAF, DASH, HLS, RTP, MPEG-TS, SMPTE ...

Planet

Data Visualization Engineer

San Francisco, CA · On-site +1

  • Medical

  • Dental

  • Vision

  • PTO

We are looking for a spatial thinker with a passion for remote sensing analysis and visual ... Comprehensive Medical, Dental, and Vision plans * Health Savings Account (HSA) with a company ...

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All JobsMedical Data Encoder JobsRemote Medical Data Encoder JobsRemote Medical Data Encoder Jobs in California

Remote Medical Data Encoder information

What is the difference between Remote Medical Data Encoder vs Remote Medical Coder?

AspectRemote Medical Data EncoderRemote Medical Coder
CertificationsTypically AHIMA or AAPC certification, coding credentialsSame certifications, often AHIMA or AAPC
Work EnvironmentRemote, healthcare facilities, insurance companiesRemote, hospitals, clinics, insurance companies
Job FocusConverting medical records into coded data for databasesAssigning codes to diagnoses and procedures for billing
Industry UsageHealthcare, insurance, data managementHealthcare, billing, insurance claims

Both roles require similar certifications and work remotely within healthcare settings. The main difference is that Remote Medical Data Encoders focus on converting medical records into coded data for databases, while Remote Medical Coders assign codes directly for billing and insurance purposes. Understanding these distinctions helps job seekers identify the best fit for their skills and career goals.

What are the most commonly searched types of Medical Data Encoder jobs in California?

The most popular types of Medical Data Encoder jobs in California are:

What are popular job titles related to Remote Medical Data Encoder jobs in California?

For Remote Medical Data Encoder jobs in California, the most frequently searched job titles are:

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The top searched job categories for Remote Medical Data Encoder jobs in California are:

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Cities in California with the most Remote Medical Data Encoder job openings:

Remote Medical Data Encoder jobs near you
Infographic showing various Remote Medical Data Encoder job openings in California as of August 2026, with employment types broken down into 79% Full Time, 11% Part Time, 5% Contract, and 5% Nights. Highlights an 11% In-person, and 89% Remote job distribution.

Staff Machine Learning Engineer, Computer Vision

Pinterest

San Francisco, CA • On-site, Remote

Full-time

Re-posted 6 days ago

Job description

Within Pinterest, the Pinterest Labs organization focuses on applied ML research and development. Labs works across a broad variety of AI/ML initiatives-including core computer vision, multimodal representation learning, heterogeneous graph neural networks, generative modeling, and recommender systems. This is the group that develops the foundation ML models that fully leverage the tens of billions of Pins and the associated knowledge graph to improve the core product.

We are currently hiring for the Visual Modeling team in Labs, which develops Pinterest's in-house visual encoder. In this role, you'll work with Pinterest's rich visual-text dataset to train large-scale models from scratch that are continuously shipped to production to power visualization features. You'll build multimodal representations that power applications such as recommender systems, Semantic IDs, and a range of downstream ML models. The visual encoder also produces visual tokens that power our in-house VLM and composed image retrieval models. The core visual pod is a small group (~10 engineers) inside Labs, which allows for deep collaboration. For example, engineers working on multimodal representation also contribute to our internal text-to-image generation Canvas project-collaborating on autoencoder design or on reward function development for RL training.

What you'll do:

  • Prototype state-of-the-art visual encoders that power Pinterest's recommender systems and internal visual language models.
  • Experiment with billion-scale datasets and gain hands-on experience with large-scale GPU computing.
  • Build flexible visual reasoning tools such as composed image retrieval, promptable detection/segmentation, and instruction-tuned embedding and generative models.
  • Read research papers, participate in group discussions, and help brainstorm the company's overall visual generative strategy.
  • Help collect relevant visual instruction training data that can be shared across multimodal representation, composed image retrieval, text-to-image generation and visual language modeling.
  • Publish and share your work through conferences, paper submissions, and blog posts.
  • Mentor junior researchers and research interns within the Pinterest Labs organization.
  •  

What we're looking for:

  • Research engineers and scientists with experience building and training computer vision models.
  • Experience with multimodal representations and visual language modeling is strongly preferred.
  • A track record of research contributions (e.g., publications, open-source work) and/or shipping ML models to production.
  • Hands-on experience with large-scale model training and modern deep learning frameworks (e.g., PyTorch).
  • Strong collaboration skills and a demonstrated ability to work effectively in a small, fast-moving team.
  • M.S. or PhD in Machine Learning or related academic areas, or equivalent work experience.
  • Publications at top ML conferences
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring

Relocation Statement:

  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

  • We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
  • This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

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