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Salesforce

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4.1

based on 811 Reviews

103 Salesforce Jobs

Data Annotation Specialist

Salesforce

4.1

based on 811 Reviews

2-7 years

Hyderabad / Secunderabad, Bangalore / Bengaluru

1 vacancy

Data Annotation Specialist

Salesforce

posted 5hr ago

Job Role Insights

Flexible timing

Key skills for the job

Data Entry Manual Testing Software Configuration Management Salesforce Research Machine Learning

+ 1 more

Job Description

Salesforces Office of Ethical and Humane Use is looking for a detail-oriented, responsible AI focused Data Annotation Specialist to join our team. Our Testing, Evaluation, and Alignment teams partner with Einstein product and engineering teams and Salesforce AI Research teams on the development of AI technology by ensuring they are built and deployed in alignment with OEHU s guidelines and policies.

The Role

As a Data Annotation Specialist, you will play a crucial role in labeling, tagging, and categorizing various types of data to facilitate testing, evaluation, alignment, and training of AI models and systems. Your primary responsibility will be to ensure high-quality annotated datasets that contribute to the development of responsible AI and trusted machine learning solutions.

The ideal candidate will be familiar with machine learning techniques to provide actionable insights on how to bring them into production. They build and use tools to ensure fair, accountable, transparent, and explainable AI. This individual will support our culture of being proactive, thoughtful, and knowledgeable about the responsible development and use of Salesforce s AI products.

Job Responsibilities :

Accurately label machine learning data through various methods to refine AI models and systems. This will primarily involve annotating large volumes of textual data according to predefined guidelines.
Lead the labeling of test data in partnership with OEHU and partner teams
Assist in data curation to develop safety detectors and guardrails.
Validate any synthetic data generation, crowdsource, or contractor jobs for labeling or data creation
Collaborate with team members to identify improvements to the labeling interface or labeling processes in order to drive efficiency and high-quality.

Participate in technical discussions, and drive labeling / annotation investments in responsible AI to improve model fairness and safety prior to launch
Complete assignments by deadlines while meeting team expectations and goals.

Job Requirements/Required Skills

Bachelor s degree (or equivalent work experience).
Experience in data annotation, labeling, or data entry with a strong focus on accuracy and attention to detail.
Familiarity with annotation tools and platforms (e.g., Labelbox, Amazon SageMaker Ground Truth, CVAT).
Familiarity with Responsible AI standards and best practices.
Strong reading comprehension and writing skills, with the ability to understand and interpret complex and diverse texts.
Ability to work independently, follow instructions, manage time effectively, and meet deadlines in a dynamic and fast-paced environment.
Ability to manage ambiguity, uncertainty, and changing priorities with limited resources.
Ability to accept and integrate continuous feedback while remaining professional.
Excellent verbal and written communication skills and the ability to collaborate within a multi-disciplinary team.
Quick learner and self-starter with strong problem-solving skills.
Understanding of machine learning concepts and workflows.

Desired Skills

Strong communication skills. Comfortable presenting ideas to diverse teams and individuals in multiple formats, from slide decks to informal chats.
Earns trust in relationships both internally and externally, and at all levels of the organization. Challenges the status quo to improve the productivity, effectiveness, and culture of a team - without burning bridges.
Experience working across teams of engineers, data scientists, and researchers.
Ability to creatively prioritize, stage, and sequence solutions to challenging/complex problems.
Works well under pressure, and is comfortable working in a fast-paced, ever-changing environment.
Passion for the idea that technology can be a force for social good and for ethics and fairness.
Grasp of the evolving understanding of fairness and ability to meet both state-of-the-art and global standards for fairness evaluation, particularly in generative AI