Data Labelling Jobs in Bangalore | Best Opportunity 2024

Data Labelling Jobs in Bangalore is a crucial task in machine learning and artificial intelligence, as it involves annotating data to train and improve algorithms. it provides an important center for algorithms to examine and make predictions. The manner includes annotating facts with labels, which includes figuring out items in photos, transcribing audio, or marking sentiment in text. This annotated information is then used to train fashions, making them able to recognize knowledge styles.

Salary: 26000/Pm

Location: Bangalore

Experience:3 years

Job Type: Full Time

Education: Graduate

Job Description:

Data Labelling Jobs in Bangalore, your primary responsibility is to annotate and label datasets for machine studying models. You will work carefully with records scientists and engineers to ensure superb training facts, contributing to improving modern AI technologies.

Data Labelling Jobs in Bangalore Key Responsibilities:

Data Labelling Jobs in Bangalore Data labelling Jobs are a crucial step in the process of training machine learning models. It involves annotating or tagging data to create a labeled dataset that can be used to train and evaluate algorithms. Data labeling jobs typically include various responsibilities, and here are some common tasks associated with this role.

Image Annotation: In image labelling tasks, annotators may be required to identify and outline objects within images. This could include drawing bounding boxes around objects or specifying key points on the image.

Text Annotation: Text labelling involves sentiment analysis, entity recognition, or text classification. Annotators may need to mark specific entities or sentiments within the text to train models for natural language processing.

Audio Transcription:

In audio labelling, workers transcribe spoken words or identify specific sounds. This is crucial for training speech recognition models and enhancing their accuracy.

Video Annotation:

Video labeling tasks can be diverse, including tracking object movements, identifying actions or events, and annotating specific frames for model training.

Consistency Checks:

Maintaining consistency in annotations is crucial for model training. Workers may need to follow guidelines meticulously to ensure uniformity across the dataset.

Handling Ambiguity:

Some data may present ambiguity, requiring annotators to make subjective decisions. An important aspect of the job is dealing with such situations and making informed choices.

Data Labelling Jobs Skills:

Technical Skills:

Familiarity with data annotation tools, basic programming concepts, and proficiency in relevant software and tools are essential. Knowledge of machine learning concepts can be an added advantage.

Guideline Adherence:

Ability to follow guidelines and instructions for data labeling projects, ensuring compliance with specific requirements.

Data Labelling Jobs in Bangalore

Data Understanding:

A basic understanding of different data types (text, image, audio, etc.) and the ability to interpret and categorize them appropriately.

Computer Literacy:

Proficiency in using computers and navigating through various software or tools used for data labeling. Familiarity with keyboard shortcuts and basic troubleshooting can be advantageous.

Software/Tool Proficiency:

Depending on the task, familiarity with specific Data labelling Jobs tools and software is crucial. Examples include Labelbox, Supervisely, or other industry-specific tools.

Time Management:

Efficiently managing time to meet labeling deadlines without compromising accuracy. Prioritizing tasks and optimizing workflow can enhance productivity.

Communication Skills:

Clear and effective communication, especially if working in a team. The ability to report issues, seek clarification, and provide feedback contributes to a smoother labeling process.

Teamwork:

Collaboration with other laborers or team members to maintain consistency in labelling and ensure overall project success.

Problem Solving:

The capacity to troubleshoot common issues that may arise during the labelling process, such as ambiguous instructions or technical challenges.

Adaptability: Ability to adapt to changes in project requirements, guidelines, or tools as projects evolve.

Quality Control: Implementing and adhering to quality control measures to guarantee the accuracy and reliability of labeled data.

Educational Background for Data Labelling Jobs:

A bachelor’s degree in a relevant field such as computer science, data science, mathematics, or a related discipline is often preferred. However, some entry-level positions may not require a degree