Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Strategic Project Lead – Speech & Audio AI (London)
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- Remote from
- UK
- Salary
- Undisclosed
- Department
- Project & Program Management
- Employment
- Full Time
- Experience
- Senior
- Published
- Apply before
- 27 Nov 2026
- Listing views
- 18
- Application actions
- 2
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The role, at a glance.
Appen is seeking a Strategic Project Lead to run end-to-end speech and audio AI data programs for external AI clients. The role combines project delivery, client management, annotation-workflow design, and ownership of data-quality outcomes. Key technical domains include ASR transcription, speaker diarization, TTS evaluation, conversational AI, and multilingual data operations. The successful candidate will translate ambiguous client needs into scalable guidelines, QA frameworks, staffing plans, and measurable delivery processes. This is a remote, UK-based full-time role in a fast-moving AI operations environment.
Role DNA
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Pace & Pressure
4/5Autonomy Level
4/5Communication Load
5/5Salary analysis
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Core skills
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Sample interview questions
I would first clarify the intended model use case, data sources, languages, acceptance criteria, volume, timeline, and risks. I would then create annotation guidelines, define the workflow and tooling, establish sampling and QA procedures, plan staffing, and agree on reporting cadence and escalation paths with the client.
I would use word error rate where a reference transcript is available, along with accuracy by language or accent, label-agreement rates, completeness, timestamp alignment, and error-category trends. I would segment results by annotator cohort and data type so corrective actions are targeted.
I would document the ambiguity with concrete examples and explain its likely impact on quality, schedule, or cost. I would propose clear decision options, obtain written alignment from the client, update the guidelines and training materials, and monitor early production samples to confirm consistent interpretation.
I would quickly identify whether the problem stems from unclear instructions, tooling, source data, training, or capacity. I would prioritize high-impact fixes such as calibration sessions, clarified edge-case guidance, targeted rework, and increased QA sampling, while transparently communicating any delivery trade-offs to stakeholders.
It is important to involve qualified native-language expertise, define locale-specific conventions, and avoid applying assumptions from one language to another. I would validate transcription and annotation guidance through pilots, track quality by locale, and maintain a feedback loop that captures culturally and linguistically specific edge cases.
About this role.
About the Role
The Strategic Project Lead – Speech & Audio will sit in Appen’s Operations organization and support the development of frontier AI through high-quality data programs for leading AI companies. We’re looking for someone with experience in speech, audio, or language data to own complex projects from planning through delivery.
You’ll combine project management, domain expertise, and quality ownership to help clients build and improve speech recognition systems, voice agents, and other AI applications. You’ll work closely with clients and internal teams to solve problems, refine workflows, and keep pace with a rapidly evolving AI landscape.
Your Impact
- Own end-to-end delivery across project scope, timelines, budgets, staffing, and risks.
- Manage client communication, status updates, workshops, and escalations.
- Translate client requirements into annotation guidelines, workflows, tooling, and quality standards.
- Define and monitor quality metrics, including transcription accuracy, word error rate (WER), diarization, and linguistic consistency.
- Troubleshoot quality issues and resolve ambiguous requirements with clients.
- Provide domain expertise across speech and audio workflows, advising on feasibility, evaluation methods, and tooling.
- Build reusable guidelines, SOPs, and QA frameworks while mentoring Operations Specialists.
- Support new project scoping, pilots, and capability development as speech and voice AI evolves.
What You Bring
- 1–2+ years of experience in AI data operations, project coordination, or delivery, ideally in a GenAI or frontier AI environment.
- Hands-on familiarity with at least one speech, audio, language, or conversational AI workflow.
- Experience coordinating projects or workstreams, managing stakeholders, and communicating with clients.
- Understanding of data quality, annotation workflows, and quality assurance methods.
- Ability to turn client requirements into clear guidelines, workflows, and quality standards.
- Strong problem-solving skills and the ability to manage multiple priorities in a fast-moving environment.
- Interest in current AI developments and how speech, audio, and voice-agent technologies are evolving.
Nice to Have
- Experience with ASR transcription, speaker diarization, acoustic annotation, or TTS evaluation.
- Familiarity with voice-agent scripts, IVR, dialogue design, turn-taking, or conversational evaluation.
- Experience with localization, cross-locale consistency, CJK languages, or low-resource languages.
- Bilingual or multilingual 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
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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