A

Almetra

Edge AI vision analytics for manufacturing

AI Go-live Specialist

Customer SuccessConfirmed live in the last 24 hours
Full-timeBerlin, GermanyIn-person

About the Job

Requirements

  • Two to five years of experience in a structured execution role such as implementation, quality assurance, solutions engineering, operations or industrial engineering, or data operations.
  • Ability to define success metrics, track performance, and drive iteration until results improve.
  • Detail-oriented and reliable process execution, including following all steps and maintaining clear documentation.
  • Ability to communicate concisely and escalate issues early and clearly.
  • Ownership of onboarding through completion and continued improvement after go-live.
  • Comfort with technical systems and ability to reason about symptoms and inputs; machine learning depth is not required.

Responsibilities

  • Own onboarding outcomes against success metrics and customer key performance indicators for quality, reliability, and time-to-value.
  • Execute the initial onboarding cycle using internal tools, then revisit and iterate to improve quality as new data and edge cases emerge.
  • Validate input data quality and flag issues early, including camera angle, occlusion, anonymization, variance, and missing detections.
  • Detect and document edge cases and standard operating procedure or process variance; grow a diverse dataset and keep it up to date.
  • Communicate progress, metrics movement, and blockers to stakeholders, and propose concrete next steps.
  • Improve the onboarding process over time through checklists, documentation, templates, and suggestions for tool improvements based on real usage.
  • Coordinate with installation teams to ensure camera setups support reliable onboarding and cross-station consistency.

Desired Qualifications

  • Manufacturing or process exposure.

About the Company

Almetra

Edge AI vision analytics for manufacturing

Almetra equips production lines with AI cameras to convert shop-floor video into real-time data, including cycle times, output, utilization, and micro-stoppages. Processing happens at the edge with privacy-by-design anonymisation, and the system links vision analytics with MES/PLC/ERP context to produce actionable insights rather than just dashboards. By combining line-level analytics with input from continuous-improvement engineers, it helps factories diagnose root causes of productivity losses and drive improvements. The goal is to scale the product and expand into the US, supported by funding such as the June 2026 Series A led by blisce/.

Company size
51-200
Company stage
Series A
Total funding
$22.4M
Headquarters
Berlin, Germany
Founded
2022

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