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LILT

Technical Project Manager

LILT

. Lead large-scale multilingual data collection, human-in-the-loop workflows, and LLM evaluation initiatives .

Posted 9/19/2026full-timeUnited StatesMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in managing large-scale multilingual data collection and evaluation projects, with a strong focus on AI/ML methodologies and technical project management. Proficient in SQL and experienced in optimizing project delivery and unit economics while effectively communicating with diverse stakeholders.

Highest-signal resume keywords
Technical Project ManagementLLM Training and EvaluationSQL ProficiencyAgile MethodologiesData Pipeline Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
SQLData Pipeline ManagementLLM TrainingEvaluation MethodologiesProject Unit EconomicsData AnnotationTechnical ScopingWorkflow AutomationData AnalysisRoot-Cause Analysis
Soft Skills
Strong Communication SkillsStakeholder ManagementProblem-Solving
Tools & Technologies
Business Intelligence ToolsAnnotation PlatformsAutomated Evaluation ToolsJiraAPIs
Industry Keywords
AI/MLMultilingual Data ProjectsHuman-in-the-Loop WorkflowsSFTRLHFLLM-as-a-JudgeTechnical RequirementsComplex Workflows

Tech Stack

Tools & technologies
PythonSQL

About the role

Key responsibilities & impact
  • Lead large-scale multilingual data collection, human-in-the-loop workflows, and LLM evaluation initiatives
  • Manage Applied AI data collection and evaluation projects from technical scoping through implementation, validation, delivery, and retrospective review
  • Translate technical AI requirements into structured data specifications, annotation requirements, evaluation plans, and acceptance criteria
  • Manage timelines, throughput velocity, dependencies, delivery risks, and technical blockers
  • Coordinate data collection and annotation for SFT, RLHF preference data, and model evaluation
  • Partner with engineering teams to define and validate ingestion, annotation tooling, integrations, quality checks, data generation pipelines, and delivery workflows
  • Operationalize hybrid evaluation methodologies combining human review, automated evaluation tooling, and LLM-as-a-judge frameworks
  • Investigate data, pipeline, and tooling issues and coordinate resolution with technical owners
  • Analyze throughput velocity, quality, unit economics, and supplier/delivery performance using SQL and business intelligence tools
  • Define and monitor quality standards, lead root-cause analysis, and establish delivery validation checks
  • Coordinate stakeholder acceptance of completed datasets, delivery targets, and evaluation results
  • Translate complex technical requirements into actionable plans for global contributors, vendors, and specialized SMEs
  • Communicate project status, risks, tradeoffs, unit economics, and operational risks to technical and non-technical stakeholders
  • Use contributor feedback and evaluation findings to improve internal tooling, guidelines, and dataset pipelines

Requirements

What you’ll need
  • 3–5+ years of technical project management experience in AI/ML, data platforms, or technical data operations
  • Strong understanding of LLM training and evaluation concepts, including SFT, RLHF, human evaluation, automated evaluations, LLM-as-a-judge, and red teaming
  • Proficiency in SQL
  • Working knowledge of data pipelines, structured data formats, APIs, and validation processes
  • Experience partnering with engineers to manage technical requirements, dependencies, and issue resolution
  • Proven ability to track and optimize project unit economics and delivery velocity
  • Strong communication skills, including translating technical requirements for multilingual audiences and diverse global contributor networks
  • Experience managing complex workflows using Agile, Scrum, or Kanban
  • Preferred: experience using Python or scripting tools for data analysis, workflow automation, or evaluation scripting
  • Preferred: experience managing specialized SMEs or contributor networks
  • Preferred: experience with annotation platforms, automated evaluation tools, business intelligence tools, and Jira
  • Preferred: experience delivering complex multilingual or multimodal data projects
  • Preferred: background in computer science, data science, engineering, or equivalent practical experience
  • Preferred: fluency in an additional language
  • Must be authorized to work in the United States on a full-time basis without restriction (application question)

Benefits

Comp & perks
  • Global collaboration
  • Growth opportunities
  • Leading tools
  • Human-in-the-loop reviews via LILT's global network of professional linguists
  • Equal opportunity and inclusive hiring process