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Data Annotation Intern Jobs in California (NOW HIRING)

Advanced annotation tools, workflow automation, and quality control systems that enable teams to ... Frontier Data Labeling Service : Specialized data labeling through Alignerr, leveraging subject ...

Unlike traditional crowdsourcing or data annotation, Avala dynamically orchestrates digital ... If an intern has the best idea you will take it and implement it. If you are wrong in an assumption ...

Data Annotation Intern information

What is the difference between Data Annotation Intern vs Data Labeling Specialist?

AspectData Annotation InternData Labeling Specialist
CredentialsTypically pursuing or recent graduate in related fieldRelevant experience or certifications in data labeling
Work EnvironmentInternship setting, often in tech or AI companiesFull-time or freelance roles in data annotation projects
Industry UsageCommon in tech, AI, and machine learning industriesUsed across similar industries for data preparation
Job FocusLearning and assisting with data annotation tasksPerforming detailed data labeling and quality control

While both roles involve working with data annotation, a Data Annotation Intern is typically a beginner or student gaining experience, whereas a Data Labeling Specialist is a more experienced professional focused on precise data labeling tasks. Interns often work under supervision, while specialists handle independent projects.

What is a data annotation intern?

A data annotation intern is a temporary position where individuals label or categorize data, such as images, text, or videos, to help train machine learning models. The role typically involves using annotation tools and requires attention to detail to ensure data accuracy and quality.

Is data annotation real or fake?

Data annotation is a legitimate job role involving labeling data such as images, text, or videos to train machine learning models. It requires attention to detail and often involves using specialized tools; the work is real and essential for AI development.

Does data annotation actually pay?

Data annotation internships and entry-level roles typically offer compensation, with pay rates varying based on the company, location, and experience. Many companies pay hourly or project-based wages, and some may provide stipends or bonuses for completing annotation tasks using tools like labeling software. It is common for data annotation jobs to be paid positions, especially when performed on a regular or full-time basis.

Is it hard to get hired for data annotation?

Getting hired as a data annotation intern generally depends on the company's requirements, but the process is often straightforward with basic computer skills and attention to detail. Many positions are entry-level and do not require extensive experience or certifications, making them accessible to beginners. However, strong accuracy and familiarity with annotation tools can improve chances of selection.

What are some common challenges faced by Data Annotation Interns and how can they be overcome?

Data Annotation Interns often encounter challenges such as maintaining consistency and accuracy when labeling large volumes of data, especially when guidelines evolve or when dealing with ambiguous cases. To overcome these challenges, it's important to frequently review annotation guidelines, communicate proactively with supervisors or team members for clarification, and participate in regular quality checks. Collaborating with experienced annotators and leveraging feedback provided during peer reviews can also help interns improve their accuracy and efficiency.

What are Data Annotation Interns?

Data Annotation Interns are entry-level professionals who assist in labeling and categorizing data, such as images, audio, or text, to help train machine learning models. Their work is crucial for ensuring that AI systems can accurately interpret and process various types of data. Interns typically use specialized software tools to annotate data according to specific guidelines, and they may also help with data quality checks. This position is ideal for those interested in gaining experience in artificial intelligence, data science, or related fields.

What are the key skills and qualifications needed to thrive as a Data Annotation Intern, and why are they important?

To thrive as a Data Annotation Intern, you need strong attention to detail, basic computer literacy, and familiarity with data labeling concepts, often supported by a background in computer science or related fields. Familiarity with annotation tools like Labelbox, Supervisely, or CVAT and understanding of data formats such as JSON or XML are typically required. Effective communication, time management, and the ability to follow complex guidelines are important soft skills for this role. These skills ensure high-quality, consistent data labeling, which is crucial for training accurate machine learning models.
What are the most commonly searched types of Data Annotation jobs in California? The most popular types of Data Annotation jobs in California are:
What are popular job titles related to Data Annotation Intern jobs in California? For Data Annotation Intern jobs in California, the most frequently searched job titles are:
What cities in California are hiring for Data Annotation Intern jobs? Cities in California with the most Data Annotation Intern job openings:
Infographic showing various Data Annotation Intern job openings in California as of June 2026, with employment types broken down into 86% Full Time, 11% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Software Engineer, AI Platform - Intern

Software Engineer, AI Platform - Intern

Nuro

Mountain View, CA โ€ข On-site

Other

Posted 15 days ago


Job description

Who We Areย 

Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that's why we're building a universal autonomy platform: self-driving for all roads and all rides.
Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles.
With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected.
Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors.

About the Role

As a software engineering intern, you will work closely with leading experts in the field of machine learning, robotics, and software. Depending on your skill sets and areas of interest, you will work on some or all of the following: Data Platform, Onboard Systems, ML Infrastructure, Simulation, or Technical Infrastructure teams.

About the Work

Depending on your skill set and areas of interest you will work on some or all of the following:

  • Data Platform: The Data Platform serves as a comprehensive management system for Nuro AI Driver's data, labels, and metrics, facilitating seamless access functionality. The team focuses on data annotation across various domains, including 2D/3D perception, mapping, behavior trajectory, and language/text. It also handles data ingestion and mining, employing methods such as heuristics and embedding search. Additionally, the platform supports the autonomy evaluation infrastructure by providing detailed introspection.ย 
  • Onboard Systems: Our onboard system team's software engineers provide a reliable and high-performance platform that allows our autonomy teams to integrate their autonomy software and algorithms that work across various self-driving platforms. This work requires close collaboration with our software teams, hardware teams, and systems/safety team to make sure new software and hardware work together safely and reliably and resolve onboard error and performance problems.
  • ML Infrastructure: The ML Infra team is the accelerator to our ML-first autonomy strategy. This team provides solutions to empower machine learning development in Nuro and optimize on-cloud training and onboard inference. Our solutions include a distributed training platform, ML compiler, model components libraries, e.t.c. The team provides opportunities for infra engineers to work fully embedded in ML teams to build cutting edge deep learning technologies.
  • Simulation: The Simulation team builds the simulator that allows us to develop and test our autonomous driving technology in a virtual setting. We work on the core simulator and simulation frameworks, sensor simulation, scenario generation, and solutions that combine real-world data with synthetic techniques to push the boundaries of what can be simulated, collaborating closely with teams across Autonomy and AI Platform to allow us to simulate realistically and reliably at scale.
  • Technical Infrastructure: this group owns few fundamental services for entire engineering organizations: generic compute platform to host mission-critical workflows such as data processing and simulation, storage management service which manages hundreds of PB of data, cloud infrastructure serves as IaaC which provisions and maintains all cloud resources, engineering productivity provides tools such as build and CI/CD to make engineering work more efficient.

About You

You have deep expertise and prior experience in some or many of the following areas:

  • You are a current BS or MS candidate in Computer Science, Electrical Engineering, Robotics, or a related field graduating in December 2026 or later
  • You have experience in one or more of the following areas: backend API design, applications development, large-scale distributed systems; data storage and processing systems; advanced algorithms using C++ and Python; machine learning, multithreading; x86 architecture; and software performance tuning and optimization, robotics software frameworks, different compute modalities (CPU, GPU, FPGA) etc.
  • You have strong problem solving and programming skills.

At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.