Project Manager, Applied AI

About LILT

AI is changing how the world communicates - and LILT is leading that transformation.

We're on a mission to make the world's information accessible to everyone
, regardless of the language they speak. We use cutting-edge AI, machine translation, and human-in-the-loop expertise to translate content faster, more accurately, and more cost-effectively without compromising on brand, voice, or quality.

At LILT, we empower our teammates with leading tools, global collaboration, and growth opportunities to do their best work. Our company virtues
- Work together, win together;
Find a way or make one;
Dance in the customer's shoes;
Quicker than they expect;
Quality is Job 1 - guide everything we do. We are trusted by Intel Corporation, Canva, the United States Department of Defense, the United States Air Force, ASICS, and hundreds of global Enterprises. Backed by Sequoia, Intel Capital, and Redpoint, we’re building a category-defining company in a $50B+ global translation market being redefined by AI.

We are looking for a data-driven Project Managers to lead our large-scale multilingual data collection and Large Language Model (LLM) evaluation initiatives. In this role, you will be the operational backbone of our AI development, orchestrating global teams of annotators and data specialists.

If you thrive in a fast-paced environment where you can optimize workflows for productivity, quality, and throughput
, we want to hear from you

• End-to-End Delivery: Manage the full lifecycle of AI data projects, from scoping and guidelines creation to data delivery and post-mortem analysis.

• Pipeline Management: Oversee large-scale data pipelines for multilingual data collection (audio, text, image) and LLM evaluation (RLHF, SFT, ranking, and safety testing).

• KPI Tracking: rigorously monitor and report on key performance indicators, including:

  • Throughput: Volume of data processed per hour/day.

  • Quality: Accuracy scores, Inter-Annotator Agreement (IAA), and gold-set performance.

  • Productivity: Cost-per-task and worker efficiency rates.

• Quality Control: Run QA loops, root-cause analysis for quality dips, and corrective training for annotator pools.

• Dashboards: Maintain dashboards to visualize project health and flag bottlenecks in real-time.

• Global Coordination: Manage relationships with data experts and crowd pools, ensuring adherence to SLAs regarding localized nuances and linguistic accuracy.

• Cross-Functional Collaboration: Liaise with Applied AI Technical Ops teams. Translate technical requirements into clear, actionable guidelines for non-technical annotators.

• Feedback Loops: Facilitate continuous feedback loops where data insights drive updates to annotation guidelines and model fine-tuning strategies.

• Experience: 3-5+ years of project management experience, specifically within AI/ML data operations
  .

• LLM Knowledge: Strong understanding of LLM training processes (Pre-training, SFT, RLHF) and evaluation methodologies (Human-in-the-loop, red teaming).

• Data Proficiency: Advanced proficiency in Excel/Google Sheets; ability to write SQL queries to extract and analyze performance data.

• Methodology: Proven track record using Agile, Scrum, or Kanban methodologies to manage complex workflows.

• Communication: Exceptional ability to write clear, unambiguous guidelines for multilingual audiences.

• Multilingual: Fluency in a second language is highly desirable.

• Technical Tools: Experience with data annotation platforms (e.g. Scale AI, Super Annotate) and project management tools (e.g. Jira).

• Education: Background in ML Engineering, Computer…