Project Manager, Applied AI
Lead large-scale multilingual data collection and LLM evaluation initiatives in a fast-paced AI-driven environment.
Posted by employer 3 days ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
What you'll build
- Manage the full lifecycle of AI data projects
- Oversee large-scale data pipelines for multilingual data collection
- Monitor and report on key performance indicators
- Manage relationships with data experts and crowd pools
- Facilitate continuous feedback loops
Must have
- 3-5+ years of project management experience
- Strong understanding of LLM training processes
- Advanced proficiency in Excel/Google Sheets
- Ability to write SQL queries
- Proven track record using Agile, Scrum, or Kanban methodologies
- Exceptional ability to write clear guidelines
Nice to have
- Fluency in a second language
- Experience with data annotation platforms
- Experience with project management tools
- Background in ML Engineering
- Computer Science
- Data Science
AI in the day-to-day
We use cutting-edge AI, machine translation, and human-in-the-loop expertise to translate content.
Requirements
- Experience
- 3–5 years
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Joblaze summary
The Project Manager for Applied AI at Lilt oversees the entire lifecycle of multilingual data projects, ensuring efficient data collection and evaluation for AI initiatives. This role requires expertise in managing large-scale data pipelines and a solid understanding of large language model training and evaluation processes. Ideal candidates have 3-5 years of project management experience in AI/ML, along with strong data analysis skills and familiarity with Agile methodologies. Lilt's focus on innovation and quality in AI-driven translation services makes this position critical to their mission.
Joblaze insights
Quick facts
- How much experience is required?
- 3–5 years of relevant experience for this Project Manager, Applied AI role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI/ML, Agile, Excel, Google Sheets, Kanban, SQL.
- What seniority level is this role?
- Lilt targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Project Manager, Applied AI role at Lilt.
From the original posting
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
Key Responsibilities
1. Project Management
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).
2. Quality Assurance & Performance Monitoring
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.
3. Stakeholder Management
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.
Qualifications
Essential Skills & Experience
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.
Preferred Qualifications (Nice to Haves)
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 Science, Data Science and Project Management training.
Our Tech
What sets our platform apart:
Brand-aware AI that learns your voice, tone, and terminology to ensure every translation is accurate and consistent
LILT in the News
Featured in The Software Report’s Top 100 Software Companies!
Standard company text repeated across Lilt's postings is omitted here.