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Weekend Data Annotation Jobs in California (NOW HIRING)

E-Space

Principal DV Engineer

Saratoga, CA

$120K - $220K/yr

... annotation Ability to assess whether SDF timing violations are benign or require attention ... This means that there will be times when extra hours, including nights and weekends, may be needed ...

E-Space

Principal DV Engineer

Saratoga, CA · On-site

$120K - $220K/yr

... annotation · Ability to assess whether SDF timing violations are benign or require attention ... This means that there will be times when extra hours, including nights and weekends, may be needed ...

E-Space

Principal DV Engineer

Saratoga, CA · On-site

$120K - $220K/yr

... annotation • Ability to assess whether SDF timing violations are benign or require attention ... This means that there will be times when extra hours, including nights and weekends, may be needed ...

All JobsData Annotation JobsWeekend Data Annotation JobsWeekend Data Annotation Jobs in California

Weekend Data Annotation information

What is the difference between Weekend Data Annotation vs Data Labeler?

AspectWeekend Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or flexible hours, part-timeRemote or on-site, part-time or full-time
Industry UsageAI training, machine learning projectsAI, autonomous vehicles, healthcare, retail
Search & Comparison IntentYesYes

Weekend Data Annotation and Data Labeler roles both involve labeling data for AI and machine learning. The main difference lies in scheduling; Weekend Data Annotation typically offers flexible, weekend-only hours, making it suitable for part-time workers or students. Data Labelers may work during regular hours and can be employed full-time or part-time. Both roles require similar skills and are used across industries like autonomous vehicles, healthcare, and retail. The choice depends on your availability and preferred work schedule.

Is it hard to get hired for data annotation?

Getting hired for a data annotation role generally depends on the applicant's attention to detail, basic computer skills, and ability to follow instructions. Many positions are entry-level and do not require advanced qualifications, making them accessible to a wide range of candidates. However, competition can vary based on the employer and the specific project requirements.

What are some typical challenges faced by weekend data annotation specialists, and how can they be addressed?

Weekend data annotation specialists often encounter challenges such as maintaining focus during repetitive tasks and managing tight turnaround times for projects that require quick weekend processing. To address these issues, it's helpful to take regular short breaks to reduce fatigue and to establish a clear workflow at the start of each shift. Additionally, open communication with team leads about workload and expectations can ensure priorities are clear, making it easier to manage deadlines and collaborate effectively, even outside traditional weekday hours.

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

To excel as a Weekend Data Annotation Specialist, you need strong attention to detail, consistency, and familiarity with data labeling processes, often supported by a high school diploma or equivalent. Competence with annotation tools like Labelbox, Supervisely, or proprietary platforms, and sometimes knowledge of basic coding or data formats (e.g., CSV, JSON), is typically required. Reliability, time management, and the ability to follow precise instructions are essential soft skills for this role. These skills ensure high-quality, accurate datasets that are critical for training effective machine learning models.

What are Weekend Data Annotation jobs?

Weekend Data Annotation jobs involve labeling, tagging, or categorizing data such as text, images, audio, or video, typically for use in machine learning or artificial intelligence projects. These roles are specifically scheduled for weekends, making them ideal for individuals seeking flexible, part-time work outside of standard weekday hours. Data annotators often work remotely and use specialized tools or platforms to ensure data is accurately and consistently labeled according to project guidelines. This work is crucial for training algorithms to recognize patterns and make predictions in various applications, such as self-driving cars, language translation, or content moderation.

Can I do data annotation with no experience?

Weekend data annotation roles typically do not require prior experience, as training is often provided. Basic computer skills and attention to detail are usually sufficient to get started, making it accessible for beginners. Familiarity with annotation tools can be helpful but is not always mandatory.

Are there less data annotation projects on weekends?

Data annotation projects for weekend data annotation roles often vary depending on the employer and project deadlines. Some companies may have fewer projects or lower activity levels on weekends, while others continue to assign tasks if remote work and flexible schedules are available. Overall, workload fluctuations are common and depend on project timelines and client needs.

Does data annotation actually pay you?

Data annotation jobs, including weekend data annotation roles, typically pay hourly or per task rates, with compensation varying by employer and location. Many companies offer remote work opportunities, and payment is usually processed through direct deposit or online platforms. It is a legitimate form of employment for those with attention to detail and basic computer skills.
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Weekend Data Annotation jobs near you
AI Robotics Research Engineer

AI Robotics Research Engineer

Nimble

San Francisco, CA • On-site

Full-time

Re-posted 21 days ago

Job description

Job Summary:
Nimble is an AI robotics company focused on creating an autonomous supply chain to enhance commerce efficiency. They are seeking an AI Robotics Research Engineer to design, develop, and implement robotic foundation models and reinforcement learning algorithms for multi-agent robot fleets.
Responsibilities:
• Develop and train diffusion policies, VLMs, multi-agent deep RL policies and more
• Develop data collection pipelines
• Design data annotation and labeling
• Support implementation of models into production systems
Qualifications:
Required:
• Masters or P.h.D in Robotics or Computer Science
• Experience training deep learning models for robotic manipulation or mobility
• Experience working with real robotic hardware
• Experience training models in simulation and developing simulation environments
• Experience collecting custom datasets
• Experience training on open-source datasets
• Strong track record of publishing papers and/or deploying real-world applications
• Experience with system architecture, design and development
• Must be able to work extended hours and weekends as needed
• Must be able to work in San Francisco
Company:
Nimble is building the autonomous supply chain powered by generalist superhumanoid robots. Founded in 2017, the company is headquartered in San Francisco, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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