Workforce Experience Associate / Specialist

Posted Yesterday
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Dhaka, BGD
Hybrid
Junior
Artificial Intelligence • Software
The Role
Manage end-to-end execution of LLM and multimodal annotation workflows: translate requirements, allocate and monitor contractor work, resolve operational and payment issues, drive quality and delivery metrics, conduct root-cause analyses, maintain documentation, mentor associates, and collaborate cross-functionally to scale AI data operations.
Summary Generated by Built In

About SuperAnnotate

SuperAnnotate is a San Francisco based AI company. We specialize in providing cutting-edge data pipeline solutions for Machine Learning, LLM, and GenAI solutions to large enterprise clients, helping them leverage the power of AI to transform their businesses. SuperAnnotate has a fully customizable platform for building annotation tools and workflows that AI projects demand — while unifying the management of all teams, vendors, and data in one place. We’re very proud to have products that are loved by our customers, resulting in us being listed as the highest-ranked platform on G2.

Why This Role Matters

    We are seeking a highly detail-oriented Workforce Experience Associate / Specialist to support the execution of complex Large Language Model (LLM) and multimodal annotation projects. As a Workforce Experience Associate / Specialist, you will play a key role in keeping LLM and multimodal annotation projects on track while ensuring contractors remain productive and supported after onboarding.

    This role bridges AI data operations and contractor success, helping resolve operational, technical, and payment-related issues that can impact delivery and quality. Your work will directly influence on-time delivery, data quality, and contractor experience—critical to scaling AI data pipelines for global enterprise clients.

What You Will Do

  • Own and drive the end-to-end execution of complex LLM, multimodal, and annotation workflows, ensuring adherence to project requirements, quality standards, delivery timelines, and operational priorities.
  • Translate project requirements into clear execution strategies, task structures, and actionable guidance for Associates, annotators, and QA specialists, including handling ambiguous guidelines and edge cases.
  • Manage workforce allocation across projects by assigning, prioritizing, and rebalancing tasks based on skill fit, availability, performance trends, delivery constraints, and operational risk.
  • Drive daily operations by monitoring task progress, throughput, quality metrics, and delivery health; proactively identify risks, resolve blockers, and ensure on-time project completion.
  • Serve as a key operational point of contact for Associates, annotators, and QA specialists, providing guidance, clarifications, and execution support.
  • Monitor quality and operational performance, conduct root-cause analysis of systemic issues, identify recurring error patterns, and recommend process improvements and risk mitigation strategies.
  • Escalate complex operational, contractor, and project-related issues to stakeholders with clear context, impact assessment, and proposed resolutions; act as an escalation point for Associates when deeper analysis or cross-functional coordination is required.
  • Manage post-onboarding contractor issues, including execution blockers, platform access, workflow questions, performance concerns, and payment-related inquiries, coordinating with Support, Engineering, Finance, Talent, and other stakeholders to ensure timely resolution.
  • Maintain accurate documentation, reporting, and issue tracking related to project execution, quality outcomes, operational metrics, contractor support, and key learnings.
  • Contribute to the continuous improvement of SOPs, operational playbooks, communication templates, and workflow processes to support scalable and efficient AI data operations.
  • Support and mentor AI Workforce Experience Associates by sharing best practices, providing operational guidance, and assisting with complex issue resolution.
  • Collaborate cross-functionally to build a scalable, reliable, and contractor-friendly AI data operations environment that delivers high-quality outcomes for global enterprise clients.

What You Will Bring

  • Educational Background: Bachelor’s degree in any relevant field
  • English proficiency: C2 level (Proficient / Near-Native) required.
  • Experience: 1-3 years
  • Strong understanding of annotation workflows, especially for LLM, NLP, vision-language, or multimodal projects.
  • High proficiency in task tracking using spreadsheets and collaboration tools.
  • Strong organizational skills with the ability to manage multiple task streams simultaneously.
  • Proactive problem-solver with a keen eye for operational gaps and execution risks.
  • Experience with Slack, Discord, Jira, or similar collaboration/project tools is a plus.
  • Familiarity with data annotation platforms and QA workflows.
  • A basic understanding of LLM or multimodal AI concepts is a strong advantage.
  • Exposure to scripting or automation (e.g. Python, Sheets formulas) is a plus.

Why Join Us?

  • Work on cutting-edge LLM and multimodal AI projects used by global enterprise clients.
  • Gain hands-on exposure to real-world AI data operations at scale.
  • Build strong operational, coordination, and problem-solving skills in a fast-growing AI infrastructure environment.

Work Schedule & Location

  • 24/7 operational environment supporting global AI projects.
  • Location: Mirpur DOHS (Remote and/or Hybrid)

Schedule and Shifts

  • Any 5 working days per week (rostered), which may include weekends based on operational requirements.
  • Rotational shifts aligned with 24/7 operational requirements.
  • Shifts will be assigned based on project needs and team rostering, with advance notice provided.

Skills Required

  • Bachelor's degree in any relevant field
  • English proficiency: C2 (Proficient / Near-Native)
  • 1-3 years of relevant experience
  • Strong understanding of annotation workflows for LLM, NLP, vision-language, or multimodal projects
  • High proficiency with task tracking using spreadsheets and collaboration tools
  • Strong organizational skills and ability to manage multiple task streams
  • Proactive problem-solving and ability to identify operational gaps and risks
  • Familiarity with data annotation platforms and QA workflows
  • Experience with Slack, Discord, Jira or similar collaboration/project tools
  • Basic understanding of LLM or multimodal AI concepts
  • Exposure to scripting or automation (e.g., Python, Sheets formulas)
  • Willingness to work rotational shifts in a 24/7 operational environment (may include weekends)
Am I A Good Fit?
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The Company
HQ: San Francisco, CA
134 Employees
Year Founded: 2018

What We Do

The end-to-end platform to annotate, version, and manage ground truth data for your AI.

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