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Manager, Data Annotation

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Job Category

Data

Job Details

About Salesforce

We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.

Salesforce AI Research seeks a top-tier professional to serve as the Manager of our Data Annotation team. We are at the forefront of Enterprise AI, demonstrating the power of large foundation models to redefine the business. Join us in paving the path to a more connected, committed, and data-driven world.

Purpose
The Manager of the Data Annotation team will lead a dedicated team responsible for collecting, cleaning, and annotating diverse datasets that fuel the training and fine-tuning of large-scale generative models.

Key Responsibilities

  • Own the creation of new data labeling tasks: define labeling guidelines based on requests from AI researchers and product engineers, onboard data annotators into the data labeling pipeline, and work with researchers to incorporate new datasets into the training of our neural networks.

  • Build machine-assisted and fully-automated tools to increase the growth rate, quality, and diversity of datasets.

  • Develop and maintain processes to ensure datasets are high quality and that annotators are consistent and adhere to labeling instructions.

  • Grow the data annotation team and foster a culture of collaboration, innovation, and continuous learning.

  • Implement robust data governance policies, including ensuring compliance with legal and ethical considerations surrounding data use.

  • Liaise with team members and partners to see opportunities for data-driven initiatives and collaborations.

  • Supervise the latest developments in machine learning, actively promoting the integration of innovative approaches into our data pipeline processes.

Qualifications

  • Familiarity with labeling tasks for language + vision understanding and experience working with third party data annotation vendors.

  • Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

  • Proven ability to lead and deliver large-scale projects on time and within budget.

  • Exceptional leadership skills with a track record of building and managing high-performing teams.

  • A related technical degree required.

Preferred Qualifications

  • Proficiency in Python and data manipulation tools like Hadoop, Spark, or Kafka.

  • Proficiency in data engineering, data science, or related roles in a leadership capacity.

  • Experience building and optimizing large-scale data pipelines and datasets.

In office expectations are 10 days/a quarter to support customers and/or collaborate with their teams.

Accommodations

If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form.

Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

For California-based roles, the base salary hiring range for this position is $145,200 to $199,700.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, benefits. More details about our company benefits can be found at the following link: https://www.salesforcebenefits.com.
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Average salary estimate

$172450 / YEARLY (est.)
min
max
$145200K
$199700K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Manager, Data Annotation, Salesforce

Are you ready to step into a leadership role that makes a difference? Salesforce, the Customer Company based in Palo Alto, California, is on the lookout for a passionate and skilled Manager of Data Annotation to join our thriving AI Research team. In this role, you’ll lead a team dedicated to collecting, cleaning, and annotating diverse datasets that are pivotal for training and fine-tuning large-scale generative models. Imagine driving powerful AI initiatives and having the chance to shape the future of business as we know it! You’ll be responsible for establishing new data labeling tasks, building innovative tools to enhance the quality and diversity of datasets, and fostering a culture of collaboration within your team. With your leadership skills, you’ll ensure that our data annotation processes are efficient and compliant with all legal and ethical standards. If you have experience in data tasks related to language and vision understanding, along with exceptional communication skills to bridge the technical gap with stakeholders, you might be the perfect fit! Join us at Salesforce, where together, we can create a more connected, committed, and data-driven world while empowering your professional growth in an inclusive environment.

Frequently Asked Questions (FAQs) for Manager, Data Annotation Role at Salesforce
What responsibilities does the Manager, Data Annotation at Salesforce have?

The Manager, Data Annotation at Salesforce is responsible for leading a dedicated team that collects, cleans, and annotates datasets necessary for training large generative models. This includes creating data labeling tasks, onboarding annotators, building automated tools for data management, and ensuring data quality and compliance with ethical standards.

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What qualifications are required for the Manager, Data Annotation position at Salesforce?

For the Manager, Data Annotation position at Salesforce, candidates need a related technical degree and experience with data annotation tasks, particularly for language and vision understanding. Strong leadership skills, excellent communication abilities, and a proven track record of managing large-scale projects are also essential.

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How does Salesforce support the growth of its Data Annotation team?

Salesforce fosters a collaborative and innovative culture within its Data Annotation team by emphasizing continuous learning and professional development. The Manager will play a key role in mentoring team members and implementing processes that encourage team growth and high performance.

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What tools and technologies should the Manager, Data Annotation be proficient in at Salesforce?

The Manager, Data Annotation at Salesforce should be proficient in Python and familiar with data manipulation tools like Hadoop, Spark, or Kafka. A background in data engineering or data science is also preferred, especially experience in building large-scale data pipelines.

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What is the work environment like for the Manager, Data Annotation position at Salesforce?

The work environment for the Manager, Data Annotation at Salesforce is collaborative and innovation-driven. There are in-office expectations of 10 days per quarter to support customer needs and enhance team collaboration. Salesforce is committed to creating an inclusive workplace where every employee can thrive.

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Common Interview Questions for Manager, Data Annotation
How do you ensure quality in data annotation projects?

To ensure quality in data annotation projects, it is important to develop clear labeling guidelines, train annotators effectively, and implement consistency checks throughout the annotation process. Regular audits and feedback loops further enhance quality management.

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Can you describe your experience with data labeling tools?

When discussing experience with data labeling tools, it's essential to mention specific software you've used, such as Labelbox or Prodigy, and how you've leveraged these tools to optimize data annotation workflows for previous projects.

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How do you manage a team of data annotators?

Managing a team of data annotators involves fostering open communication, setting clear expectations, providing constructive feedback, and encouraging a collaborative atmosphere where team members feel valued and capable of contributing their best work.

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What challenges have you faced in data annotation projects and how did you overcome them?

Challenges in data annotation often include dataset inconsistency or complex labeling tasks. Overcoming these requires a proactive approach, such as refining guidelines, conducting team workshops, or employing automated tools to alleviate manual workload.

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How do you handle tight deadlines in data annotation projects?

Handling tight deadlines involves prioritizing tasks effectively, ensuring that resources are allocated efficiently, and maintaining open lines of communication with stakeholders to manage expectations and timelines.

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What is your approach to integrating new datasets into existing pipelines?

Integrating new datasets involves thorough planning, creating robust documentation, and adhering to standardized procedures to ensure seamless integration into existing data pipelines while minimizing disruption to ongoing tasks.

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Can you explain the importance of data governance in a data annotation context?

Data governance in data annotation is critical to ensure compliance with legal and ethical standards. It involves establishing clear policies around data use, ensuring proper handling and storage of data, and safeguarding sensitive information throughout the annotation process.

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What metrics do you use to evaluate the success of data annotation projects?

Success in data annotation projects can be measured using metrics like annotation accuracy, completion time, and annotator performance. Regular assessments using these metrics help identify areas for improvement and ensure project goals are met.

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How do you stay updated with the latest developments in machine learning?

Staying updated with machine learning developments can involve following industry publications, attending conferences, participating in webinars, and engaging with online communities to learn about new techniques and tools relevant to data annotation.

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What strategies do you employ to build a cohesive team among data annotators?

Building a cohesive team involves promoting collaboration through team-building activities, setting shared goals, and encouraging open communication. Recognizing individual contributions also strengthens team morale and unity.

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DATE POSTED
April 15, 2025

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