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Internship Medical Data Annotation Jobs (NOW HIRING)

Cartesia

Human Data Operations Manager

San Francisco, CA · On-site

$160K - $190K/yr

Own relationships with vendors such as data annotation firms and contractor platforms, negotiating ... Fully covered medical insurance along with dental and vision for you and your family. 401(k) ...

Sesame

Technical Program Manager, Data

San Francisco, CA · On-site

$200K - $260K/yr

Lead audio data collection and annotation efforts at Sesame. * Collaborate with research and ... Flexible spending account with employer matching up to $1,650/year (medical FSA) * Guardian ...

xAI

AI Healthcare and Administration Tutor

... teams to improve annotation tools and curate impactful data. Responsibilities : • Utilize ... medical billing, administrative workflows, and healthcare operations. • Collaborate with ...

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Internship Medical Data Annotation information

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$42

How much do internship medical data annotation jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for internship medical data annotation in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is the meaning of internship?

An internship is a temporary position that provides practical work experience in a specific field, such as medical data annotation. Interns typically assist with tasks under supervision to develop skills and gain industry knowledge, often as part of educational or training programs. It can be a valuable step toward a full-time career in the field.

Is a 3.4 GPA good for internships?

For an internship in medical data annotation, a 3.4 GPA is generally considered acceptable, especially if combined with relevant skills such as attention to detail and familiarity with data annotation tools. Many employers prioritize practical skills and experience alongside GPA, so demonstrating proficiency can be more important than the exact GPA score.

What is the difference between an attachment and an internship?

An internship is a temporary, structured work experience designed for skill development and career exploration, often involving training and mentorship. An attachment typically refers to a document or file added to an application or report, and in some contexts, it can also mean a short-term work placement or observation period. In the context of a Medical Data Annotation internship, it involves hands-on labeling of medical data to improve AI models, while an attachment is a supporting document or file related to the role.

Is $30 an hour good for an intern?

For an internship in medical data annotation, $30 an hour is considered above average, as most internships pay lower rates or offer stipends. However, pay can vary based on location, required skills, and the complexity of annotation tasks. Interns should also consider the experience gained and potential for future opportunities when evaluating compensation.

What is the difference between Internship Medical Data Annotation vs Medical Data Labeling Specialist?

AspectInternship Medical Data AnnotationMedical Data Labeling Specialist
CredentialsTypically students or entry-level with basic knowledgeRelevant certifications or experience in data annotation
Work EnvironmentInternship programs, often in healthcare or tech companiesFull-time or part-time roles in healthcare tech firms
Industry UsageUsed for training and educational purposes, entry-level projectsOperational roles focusing on data accuracy and labeling

Internship Medical Data Annotation roles are usually entry-level positions designed for students or newcomers to gain experience, often within internship programs. Medical Data Labeling Specialists are more experienced roles focused on precise data annotation for AI training, requiring relevant skills or certifications. While both involve working with medical data, internships are more educational, whereas specialists handle ongoing, professional data labeling tasks.

More about Internship Medical Data Annotation jobs
What cities are hiring for Internship Medical Data Annotation jobs? Cities with the most Internship Medical Data Annotation job openings:
What are the most commonly searched types of Medical Data Annotation jobs? The most popular types of Medical Data Annotation jobs are:
What states have the most Internship Medical Data Annotation jobs? States with the most job openings for Internship Medical Data Annotation jobs include:
What job categories do people searching Internship Medical Data Annotation jobs look for? The top searched job categories for Internship Medical Data Annotation jobs are:
Internship Medical Data Annotation jobs near you
Infographic showing various Internship Medical Data Annotation job openings in the United States as of June 2026, with employment types broken down into 1% Locum Tenens, 4% As Needed, 92% Full Time, 2% Part Time, and 1% Nights. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Human Data Operations Manager

Cartesia, Inc.

San Francisco, CA

Other

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago

Job description

About Cartesia
Our mission is to architect AI that learns from and interacts with the world like humans do.
We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences.
We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI.
The Role
We are looking for a Human Data Operations Manager to design, scale, and operate Cartesia's global scaled evaluation workforce. This role sits at the intersection of product operations, data operations, and vendor management, and directly impacts model quality and customer outcomes. You will own the end-to-end workforce system: hiring pipelines, vendor strategy, workforce planning, quality control, and operational performance.
You are building a production system of humans-in-the-loop for AI, translating ambiguous product needs into operational workflows and partnering across product, engineering, data, and customer-facing teams to support real-world evaluation at scale.
Your Impact
  • Design and implement workforce structure across languages, skill tiers, and use cases, including evaluators, auditors, and leads for TTS products
  • Build capacity models to support continuous eval pipelines and data production workflows
  • Own relationships with vendors such as data annotation firms and contractor platforms, negotiating rate cards, SLAs, and throughput guarantees
  • Decide on build, buy, or hybrid workforce models and continuously benchmark cost and performance across regions
  • Design multi-layer QA systems spanning self-checks, peer review, audits, and gold tasks
  • Define and track inter-rater reliability, error rates by category, and annotator-level performance distributions
  • Build escalation and retraining workflows to maintain quality at scale
  • Run day-to-day operations including task allocation, throughput tracking, and SLA adherence
  • Build systems to reduce evaluator fatigue, rotate task types, and maintain consistency across large-scale evaluations
  • Partner with tooling teams to improve evaluator UX and with data teams to ensure clean, structured outputs for model training
What You Bring
  • 5+ years in operations, workforce management, or data annotation systems
  • Experience managing large contractor or vendor-based workforces
  • Proven ability to scale operations from zero to production
  • Systems thinking with the ability to design scalable operational frameworks
  • Strong analytical skills with comfort around metrics like inter-rater reliability, precision, and throughput
  • Ability to execute quickly under ambiguity with close attention to quality and edge cases
Nice to Have
  • Experience in AI/ML data operations or evaluation pipelines
  • Background in audio, speech, or language-related workflows
  • Familiarity with QA systems and annotation tooling
  • Experience with marketplace platforms such as Upwork or Mercor
  • Exposure to multilingual operations

More Details
In-office policy: We're an in-person team based out of offices in S San Francisco, GB London and I Bangalore. We love being in the office, hanging out together, and learning from each other every day.
Visa sponsorship: We provide visa sponsorship support and assess each circumstance on a case-by-case basis. However, visa sponsorship is dependent on many factors, including the role you are applying for, and the location you are going to be based, and so we can't always guarantee success. Your Recruiter will work with you to understand your visa sponsorship needs from the first call.
We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. We have a high bar, and we don't sacrifice quality or design along the way.
We support each other. We have an open & inclusive culture that's focused on giving everyone the resources they need to succeed.
Our Benefits (US Employees Only)
Compensation. Competitive base salary alongside attractive equity package.
Health Insurance. Fully covered medical insurance along with dental and vision for you and your family.
401(k)
Commuter Allowance. A monthly stipend to help you get to and from the office.
Flexible PTO. Take as much time as you need to recharge your batteries.
Meals & Snacks. Lunch, dinner and plenty of snacks, provided daily.
Your own personal Yoshi.

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