4 дня назад
Project Manager (AI/ML)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Project Manager (AI/ML): Managing large-scale multilingual data collection and LLM evaluation initiatives with an accent on end-to-end delivery, quality control, KPI tracking, and global annotator coordination. Focus on optimizing data pipelines, translating technical requirements into annotation guidelines, and using performance insights to improve model fine-tuning strategies.
Location: Remote in the USA
Company
develops AI-powered translation and language technology using machine translation, large language models, and human-in-the-loop systems.
What you will do
- Manage the full lifecycle of large-scale AI data projects, from scoping and guideline creation through delivery and post-mortem analysis.
- Oversee multilingual data collection pipelines covering audio, text, and image data, as well as LLM evaluation workflows including RLHF, SFT, ranking, and safety testing.
- Track throughput, quality, productivity, cost-per-task, worker efficiency, Inter-Annotator Agreement, and gold-set performance.
- Run quality assurance loops, perform root-cause analysis, and coordinate corrective training for annotator pools.
- Maintain project-health dashboards, identify bottlenecks, and manage relationships with data experts and crowd pools against SLA requirements.
- Collaborate with Applied AI Technical Operations teams and convert technical requirements into clear guidelines for non-technical annotators.
Requirements
- 3–5+ years of project management experience in AI/ML data operations.
- Strong understanding of LLM training processes, including pre-training, SFT, and RLHF, plus human-in-the-loop evaluation and red teaming.
- Advanced proficiency with Excel or Google Sheets and the ability to write SQL queries for performance analysis.
- Experience managing complex workflows with Agile, Scrum, or Kanban methodologies.
- Ability to write clear, unambiguous guidelines for multilingual audiences.
- Background in ML Engineering, Computer Science, Data Science, or project management training.
Nice to have
- Fluency in a second language.
- Experience with data annotation platforms such as Scale AI or SuperAnnotate.
- Experience with project management tools such as Jira.
Culture & Benefits
- Remote work with global collaboration.
- Opportunities for professional growth and access to leading tools.
- Work guided by principles focused on collaboration, customer empathy, speed, problem-solving, and quality.
- Work on AI, machine translation, human-in-the-loop systems, and agentic AI products.
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