3h ago

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Strategic Project Lead - Speech & Audio AI

United StatesRemoteFull-timelead

OperationsProject Manager

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Quick Summary

Requirements Summary

Manage project scope, timelines, budgets,

Technical Tools

OperationsProject Manager

Join a forward-thinking AI operations team dedicated to advancing next-generation artificial intelligence through high-quality speech, audio, and language data programs. In this role, you will lead complex projects from initial planning through final delivery, helping global clients develop and improve speech recognition systems, voice agents, and conversational AI applications. You will combine project management expertise, domain knowledge, and quality assurance to ensure reliable, scalable, and impactful outcomes. Working closely with clients and cross-functional teams, you will translate technical requirements into practical workflows, clear annotation guidelines, and measurable quality standards. You will also help resolve complex data challenges, optimize delivery processes, and develop reusable operational frameworks. This remote opportunity offers the chance to contribute to cutting-edge AI innovation in a collaborative, international environment that values curiosity, accountability, and continuous learning.

Lead end-to-end project delivery: Manage project scope, timelines, budgets, staffing, resource allocation, and risks to ensure speech and audio AI programs meet client expectations and delivery objectives.

Manage client relationships: Serve as a primary point of contact for client communications, status updates, workshops, project reviews, and escalations, maintaining alignment throughout the project lifecycle.

Translate requirements into operational workflows: Convert client objectives into clear annotation guidelines, project processes, tooling requirements, and quality standards that support consistent execution.

Monitor data quality and performance: Define, track, and analyze key quality metrics, including transcription accuracy, word error rate (WER), speaker diarization, and linguistic consistency.

Resolve quality and delivery challenges: Investigate data quality issues, clarify ambiguous requirements with clients, and implement corrective actions to improve project outcomes.

Provide speech and audio expertise: Advise clients and internal teams on workflow feasibility, evaluation methodologies, tooling options, and best practices across speech, audio, and conversational AI projects.

Develop operational standards: Create and maintain reusable guidelines, standard operating procedures (SOPs), quality assurance frameworks, and documentation to improve efficiency and scalability.

Support team development: Share domain knowledge, mentor Operations Specialists, and promote consistent execution and quality practices across project teams.

Contribute to business and capability development: Support project scoping, pilot programs, and new service development as speech recognition, voice agents, and other AI technologies evolve.

Drive continuous improvement: Identify opportunities to refine processes, strengthen quality controls, and adapt delivery approaches to emerging client needs and industry developments.

Requirements

~2 min read

Relevant professional experience: At least 1–2 years of experience in AI data operations, project coordination, project delivery, or a related field, ideally within generative AI or frontier AI environments.

Speech and language expertise: Practical familiarity with at least one speech, audio, language data, or conversational AI workflow.

Project and stakeholder management: Experience coordinating projects or workstreams, managing competing priorities, and communicating effectively with clients and internal stakeholders.

Data quality and annotation knowledge: Understanding of data annotation processes, quality assurance methods, and the importance of accuracy and consistency in AI training and evaluation datasets.

Requirements translation: Ability to transform client needs into actionable guidelines, operational workflows, evaluation criteria, and measurable quality expectations.

Analytical and problem-solving skills: Strong critical thinking, attention to detail, and the ability to investigate issues, resolve ambiguities, and make sound decisions in a fast-paced environment.

Organizational skills: Ability to manage multiple projects and deadlines while maintaining quality, accountability, and clear communication.

Interest in AI innovation: Curiosity about emerging AI developments and a genuine interest in the evolution of speech technologies, audio processing, and voice-agent applications.

Preferred speech and audio experience: Familiarity with automatic speech recognition (ASR), transcription, speaker diarization, acoustic annotation, or text-to-speech (TTS) evaluation.

Preferred conversational AI knowledge: Experience with voice-agent scripts, interactive voice response (IVR), dialogue design, conversational evaluation, or turn-taking analysis.

Preferred multilingual capabilities: Experience with localization, cross-language consistency, CJK languages, or low-resource languages is an advantage. Bilingual or multilingual proficiency, particularly in German or a Nordic language, is also desirable.

Collaborative mindset: Ability to work effectively across international teams, share knowledge, adapt to changing requirements, and maintain a strong focus on client satisfaction and delivery quality.

What We Offer

~2 min read

Remote work: Flexibility to work remotely from the United States.

Full-time employment: A permanent opportunity to contribute to long-term AI projects and operational initiatives.

Cutting-edge AI projects: The opportunity to support the development, training, and evaluation of advanced AI models, speech recognition systems, and voice-agent technologies.

International collaboration: Work alongside talented professionals and global teams on projects serving clients across industries and geographies.

Professional development: Access to tools, resources, and opportunities to expand your technical knowledge, project management expertise, and AI domain capabilities.

Collaborative culture: Join an environment that values innovation, curiosity, humility, accountability, and shared success.

Meaningful impact: Help improve the quality and reliability of AI systems through high-quality data programs and scalable operational processes.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1

✓Remote work: Flexibility to work remotely from the United States.

✓Full-time employment: A permanent opportunity to contribute to long-term AI projects and operational initiatives.

✓Cutting-edge AI projects: The opportunity to support the development, training, and evaluation of advanced AI models, speech recognition systems, and voice-agent technologies.

✓International collaboration: Work alongside talented professionals and global teams on projects serving clients across industries and geographies.

✓Professional development: Access to tools, resources, and opportunities to expand your technical knowledge, project management expertise, and AI domain capabilities.

✓Collaborative culture: Join an environment that values innovation, curiosity, humility, accountability, and shared success.

✓Meaningful impact: Help improve the quality and reliability of AI systems through high-quality data programs and scalable operational processes.