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Strategic Project Lead – Multimodal AI (United States)

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Remote from
USA
Salary
Undisclosed
Employment
Full Time
Experience
Senior
Published
Apply before
30 Nov 2026
Listing views
50
Application actions
2
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AI Summary

The role, at a glance.

Appen is seeking a Strategic Project Lead to deliver multimodal AI data programs for frontier AI clients. The role owns project scope, schedules, budgets, staffing, risks, quality metrics, and client communications. It requires practical familiarity with image, video, 3D, sensor, robotics, or related annotation workflows, alongside strong stakeholder coordination. The successful candidate will translate technical requirements into collection and labeling processes, quality standards, SOPs, and reusable QA frameworks. This is a remote, US-focused full-time role in a fast-moving AI data operations environment.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThe position combines end-to-end delivery accountability with specialized multimodal data knowledge and frequent resolution of ambiguous client requirements. Managing quality, operational risks, and multiple stakeholders in a rapidly changing AI environment makes the work demanding.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$102,000
US market range (per year)$85k–$120k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary was disclosed. For a US-based full-time strategic project lead with AI data operations and multimodal annotation expertise, the estimated annual market range is USD 85,000–120,000, with an estimated midpoint of USD 102,000. The annual cadence is inferred from the full-time US professional role and standard market convention.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you turn a client's ambiguous multimodal data request into an executable annotation workflow?

I would first clarify the use case, target model behavior, data modalities, edge cases, acceptance criteria, and delivery constraints. I would then create a pilot workflow with detailed labeling instructions, examples, tooling requirements, quality checks, and measurable success criteria before scaling production.

What metrics would you use to assess quality in an image, video, or sensor annotation project?

I would combine inter-annotator agreement, gold-set accuracy, defect rates, rework rates, coverage of required scenarios, and turnaround time. The precise thresholds would be aligned with the client's use case and documented in the acceptance criteria.

Describe how you would manage a project that is falling behind schedule without compromising quality.

I would identify the source of the delay through data, staffing, tooling, and workflow analysis, then prioritize the highest-impact corrective actions. Depending on the findings, I would rebalance capacity, simplify unclear instructions, address tooling blockers, run targeted retraining, and communicate a revised recovery plan and risks to the client.

How do you handle conflicting requirements from internal teams and a client?

I document the conflict, assess its impact on scope, quality, timeline, and cost, and bring the relevant decision-makers together with clear options. Once a decision is made, I update the requirements, workflow documentation, and delivery plan so that every team works from the same source of truth.

What experience or approach would you bring to multimodal data involving 3D, point clouds, or robotics sensors?

I would focus on understanding sensor provenance, coordinate systems, temporal alignment, labeling ontology, and downstream model requirements. I would validate the workflow through representative samples and edge cases, ensuring that instructions and QA checks support consistent, usable annotations across annotators and data sources.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

About the Role

The Strategic Project Lead – Multimodal AI supports frontier AI development through complex, high-quality data programs for leading AI companies. We’re looking for someone with experience in multimodal AI data, such as image, video, 3D, sensor, or robotics-related workflows.

You’ll lead projects that turn complex real-world data into reliable training and evaluation resources. Combining project management with hands-on domain knowledge, you’ll partner with clients and internal teams to design workflows, maintain quality, and solve challenging data delivery problems in a rapidly evolving AI market.

Your Impact

  • Own end-to-end project delivery across scope, timelines, budgets, staffing, and risks.
  • Lead client communication, status reporting, planning sessions, and escalations.
  • Translate technical and client requirements into data collection workflows, annotation guidelines, tooling, and quality standards.
  • Define quality metrics and acceptance criteria for multimodal data and annotation outputs.
  • Monitor delivery quality, troubleshoot data issues, and resolve ambiguous requirements with clients.
  • Advise on project feasibility, collection methods, annotation approaches, and tooling based on your domain expertise.
  • Build reusable SOPs, guidelines, and QA frameworks to support consistent delivery.
  • Mentor Operations Specialists and contribute to project scoping, pilots, and emerging multimodal AI capabilities.

What You Bring

  • 1–2+ years of experience in AI data operations, project coordination, or delivery, ideally in a GenAI or frontier AI environment.
  • Familiarity with at least one multimodal data workflow involving images, video, 3D data, sensors, or robotics.
  • Experience coordinating projects or workstreams, managing stakeholders, and communicating with clients.
  • Understanding of data quality, annotation workflows, and quality assurance methods.
  • Ability to translate project requirements into clear data collection workflows, annotation guidelines, and quality standards.
  • Strong problem-solving skills and the ability to manage multiple priorities in a fast-moving environment.
  • Interest in current AI developments, including multimodal models, spatial AI, or embodied AI.

Nice to Have

  • Experience with image or video annotation, 3D data, point clouds, or sensor data.
  • Familiarity with robotics data collection or real-world perception workflows.
  • Exposure to 2D or 3D labeling, segmentation, tracking, or structured annotation tasks.
  • Experience with autonomous systems, spatial AI, or embodied AI.
  • Bilingual capabilities, particularly German or a Nordic language.

Why You’ll Love Working Here

At Appen, we foster a culture of innovation, collaboration, and excellence. We value curiosity, accountability, and a commitment to delivering the highest quality AI solutions for frontier models.

You’ll work on complex challenges that shape the future of AI across industries and geographies, alongside talented people in a culture that values humility over ego. You’ll have the flexibility to deliver in a way that works for you and your team, supported by tools, resources, and development opportunities to continue to build your capability over time.

About Appen

Appen has been a leader in AI training data for over 30 years. We specialise in human generated data to train, fine tune, and evaluate models across generative AI, large language models, computer vision, and speech recognition. Our AI assisted data annotation platform and global crowd of more than 1 million contributors in over 200 countries support model pre training, supervised fine tuning, evaluation and benchmarking, safety and red teaming, and multilingual global expansion.

Compensation

Additional Information

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