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Internship Data Labeling Jobs in California (NOW HIRING)

Planet Pharma

Laboratory Technician

San Diego, CA

$20.25 - $26.75/hr

*Recent graduates with lab internships encouraged to apply* This company is looking for a Bottling ... labeling, kitting and completing batch records, and putting away Finished Good Inventory (FGI)

Kodiak

Fall 2026 Intern, Perception

Mountain View, CA · On-site

$17.75 - $23.50/hr

... and ultrasound data. * Collaborate closely with other experts on the team, including the AI ... Our internship program is 12-16 weeks; the end date is flexible based on individual needs.

ITW Tire Repair

Chemist Intern

San Luis Obispo, CA

$22 - $28/hr

About Our Internship Program As an intern at ITW Global Tire Repair, you'll gain hands-on ... Collect, analyze, and document experimental data and maintain accurate lab records * Review ...

MemorialCare

Registered Dietitian II

Long Beach, CA · On-site

$39.12 - $56.75/hr

The RD II acts as a mentor to dietetic interns, students, and level I RDs. Essential Functions and ... Identifies and labels specific nutrition diagnosis(es) derived from the assessment data.

Actalent

Lab Intern

Woodland, CA · On-site

$18/hr

Label samples, reagents, and equipment to ensure proper tracking * Assist with analytical tasks ... Help collect and record quantitative data on fruit and vegetable characteristics * Properly manage ...

New

MemorialCare

Registered Dietitian II

Long Beach, CA · On-site +1

$39.12 - $56.75/hr

Identifies and labels specific nutrition diagnosis(es) derived from the assessment data ... interns, level I RDs, and new staff members as assigned. Participates in nutrition-related ...

memorial care

Registered Dietitian II

Long Beach, CA · On-site

$39.12 - $56.75/hr

The RD II acts as a mentor to dietetic interns, students, and level I RDs. Essential Functions and ... Identifies and labels specific nutrition diagnosis(es) derived from the assessment data.

memorial care

Registered Dietitian II

Long Beach, CA · On-site

$39.12 - $56.75/hr

The RD II acts as a mentor to dietetic interns, students, and level I RDs. Essential Functions and ... Identifies and labels specific nutrition diagnosis(es) derived from the assessment data.

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All JobsInternship Data Labeling JobsInternship Data Labeling Jobs in California

Internship Data Labeling information

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

AspectInternship Data LabelingData Labeling Specialist
CredentialsTypically students or entry-level with basic skillsRelevant experience or certifications in data annotation
Work EnvironmentInternship programs, often in tech or AI companiesFull-time or freelance roles in data annotation firms or tech companies
Industry UsageUsed as training or entry-level positionProfessional role with ongoing responsibilities
Search & Comparison IntentUnderstanding entry-level opportunities and trainingClarifying professional roles and career progression

Internship Data Labeling is an entry-level position designed for students or beginners gaining experience in data annotation. In contrast, Data Labeling Specialist is a professional role requiring prior experience or certifications, with more responsibility and independence. Internships serve as training grounds, while specialists handle ongoing data labeling tasks in a professional setting.

What types of tasks can I expect to handle daily as a Data Labeling Intern?

As a Data Labeling Intern, your daily tasks typically include reviewing and accurately tagging data such as images, audio, or text according to specific guidelines provided by the company or project. You may use specialized annotation tools and work closely with data scientists, engineers, or QA teams to ensure high-quality, consistent labeling. Attention to detail is crucial, as your work directly impacts the performance of machine learning models. You might also participate in periodic team meetings to discuss challenges, clarify instructions, and receive feedback to improve labeling accuracy.

What is an internship in data labeling?

An internship in data labeling involves assisting in the process of categorizing and annotating data, such as images, text, or audio, to help train machine learning models. Interns typically use specialized software to tag or classify data according to specific guidelines provided by the company or research team. This role is crucial for developing accurate artificial intelligence systems, as high-quality labeled data improves model performance. Data labeling internships are a great way to gain practical experience in the AI and machine learning field and learn more about data preprocessing workflows.

What are the key skills and qualifications needed to thrive as an Internship Data Labeling specialist, and why are they important?

To excel in an Internship Data Labeling role, you need strong attention to detail, basic analytical skills, and proficiency with data entry or spreadsheet tools, often supported by a high school diploma or current university enrollment. Familiarity with labeling platforms, annotation tools, and sometimes basic programming or database systems is beneficial. Reliability, communication, and the ability to follow instructions precisely are key soft skills for standing out in this position. These skills ensure data accuracy and consistency, which are crucial for developing reliable AI and machine learning models.
What are the most commonly searched types of Data Labeling jobs in California? The most popular types of Data Labeling jobs in California are:
What are popular job titles related to Internship Data Labeling jobs in California? For Internship Data Labeling jobs in California, the most frequently searched job titles are:
What job categories do people searching Internship Data Labeling jobs in California look for? The top searched job categories for Internship Data Labeling jobs in California are:
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Internship Data Labeling jobs near you

Backend Software Engineer -- Data Platform & AI Data Products

Together AI

San Francisco, CA • On-site

Full-time

Posted yesterday

Job description

Job Summary:
Together AI is a research-driven artificial intelligence company focused on creating open and transparent AI systems. The Backend Software Engineer will join the Data Platform team to build backend services and data products that enhance data movement and self-service capabilities across the organization.
Responsibilities:
• Contribute to backend services that enhance the data platform’s capabilities (APIs, control planes, automation, governance).
• Help enable DIY workflows for teams across the company:
• Define/publish events and schemas
• Create/consume streams and subscriptions
• Establish access models (authz, row/field-level controls where applicable)
• Manage dataset/catalog metadata, lineage, versioning, and retention
• Contribute to end-to-end data products: ingestion → validation/quality → enrichment → serving (APIs/streams) → observability → adoption.
• Work on prompt categorization and enrichment services: taxonomy design, labeling workflows, classifier/rules integration, evaluation, drift/quality monitoring, and safe rollouts.
• Learn to own reliability: SLOs, alerting, performance/cost tuning, incident response, and postmortems.
• Partner cross-functionally with ML/LLM, infra, security, and product teams to define crisp contracts and deliver durable platform primitives.
Qualifications:
Required:
• 0–4 years building production or project-based backend systems (internships, coursework, and personal projects count).
• Solid fundamentals in at least one backend language (e.g., Go, Python, Java, Rust) and some exposure to API design (REST).
• Eagerness to own work end-to-end: design docs, implementation, testing, deployment, and iteration based on real usage.
• Strong engineering fundamentals: clean, maintainable code, thoughtful abstractions, and a desire to build systems that are easy to evolve.
• Basic data modeling and SQL skills, and some familiarity with at least one of: Streaming/eventing (Kafka/PubSub/Kinesis, etc.), Workflow/compute (Airflow/Spark/Flink/Trino, etc.), OLTP/OLAP stores and data lakes (Postgres + warehouse/lake tech).
• AI augmentation curiosity: You’re curious about how engineers use AI/LLMs to build software faster and better (e.g., coding copilots, agentic workflows, retrieval/knowledge grounding), and you’re eager to apply this to your own work.
• You understand that AI tools can fail or create issues, and you’re thoughtful about when and how to apply them.
Preferred:
• Any exposure to self-serve platforms, developer tooling, or multi-tenant services.
• Coursework or projects involving LLM/AI products: prompt/response telemetry, eval datasets, embeddings/RAG metadata, model/tool traces, privacy-safe logging.
• Passion for good quality code, highly readable, SOLID principles, design patterns, Domain Driven Design.
• Awareness of security and governance basics: least-privilege access, auditability, data retention, PII handling.
Company:
Together AI is a cloud-based platform designed for constructing open-source generative AI and infrastructure for developing AI models. Founded in 2022, the company is headquartered in San Francisco, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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