Production Manager, Applied AI

LILT AI
Boston, District of Columbia, Indianapolis, New York, London, San Francisco
Workplace: HybridFull timeUSD 110,000 - 145,000 annuallyFunction: Manufacturing & Production OperationsExperience: 5+ yearsSkills: ["People management","KPI-driven management","Cross-functional communication","Quality-focused execution","Process standardization"]

Own PM performance and delivery outcomes across a portfolio of AI/ML data operations programs, ensuring on-time launches, throughput, and first-pass acceptance. Build and scale a PM pool by hiring, onboarding, and developing project managers for signed demand. Detect and resolve quality dips through QA loops, remediation, and guideline updates. Standardize processes and drive software improvements from post-mortems, coordinating escalations across PM, Quality, Talent, and Delivery.

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FursaFursa
LILT AI
LILT AI
2 days ago

Production Manager, Applied AI

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Source: Company careers pageValidated by: Fursa AI
Last checked: 6 hours agoStatus: Live

Job Summary

Own PM performance and delivery outcomes across a portfolio of AI/ML data operations programs, ensuring on-time launches, throughput, and first-pass acceptance. Build and scale a PM pool by hiring, onboarding, and developing project managers for signed demand. Detect and resolve quality dips through QA loops, remediation, and guideline updates. Standardize processes and drive software improvements from post-mortems, coordinating escalations across PM, Quality, Talent, and Delivery.
Location: Boston, District of Columbia, Indianapolis, New York, London, San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: Manufacturing & Production Operations
Seniority: Manager level

Key Responsibilities

  • •Drive PM performance to ensure programs hit on-time delivery and first-pass acceptance without escalation, using monthly scorecards for throughput, quality, and cost-per-task.
  • •Manage PM pool capacity by sourcing, onboarding, ramping, and developing project managers so programs start on time and attrition stays below threshold.
  • •Lead quality interventions across programs by catching quality dips mid-program via QA loops, retraining annotator pools, updating guidelines, and executing remediation/replacement.
  • •Standardize processes and improve software by launching programs from shared playbooks/templates and turning post-mortems into documented improvements that reduce handoff-to-delivery time.
  • •Handle escalation and cross-functional interface by surfacing risks early and resolving escalations across PM pool, Quality, Talent, and Delivery within agreed timelines.

Pay and Benefits

Salary: USD 110,000 - 145,000 annually

Key Requirements

  • •5+ years in AI/ML data operations or production, including 2+ years managing project managers or team leads in a distributed, multi-time-zone contractor environment.
  • •Strong understanding of LLM training processes (pre-training, SFT, RLHF) and evaluation methodologies (human-in-the-loop, red teaming).
  • •Run teams against throughput, quality (accuracy, IAA, gold-set), and cost-per-task targets; advanced proficiency with spreadsheets and dashboards; use SQL to analyze performance data.
  • •Sustain on-time delivery and acceptance targets across multiple concurrent data collection or evaluation programs for enterprise or research lab customers.
  • •Have hired, ramped, performance-managed, and offboarded hourly/freelance staff across regions and languages.
Experience:5+ yearsAI/ML data operationsProductionDistributed workforceMultilingual data deliveriesData annotation
Skills:People managementKPI-driven managementCross-functional communicationQuality-focused executionProcess standardization
Tech Stack:LLMMachine translationHuman-in-the-loopRed teamingSQLSpreadsheetsDashboardsAgileScrumKanbanLabel StudioSuperAnnotateJiraMultimodalPre-trainingSFTRLHF

Company Brief

LILT AI
Provides an AI-powered enterprise translation and localization platform combining machine translation, adaptive learning, automation workflows, and human verification to help organizations create and manage multilingual content at scale.
Industry: SaaS
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Funding: Series C
Headquarters: San Francisco, United States
Founded: 2015
Glassdoor
Glassdoor: 3.9
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