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VoIP Engineer & AI Automation

Staffinc Affiliate - Sri Wulan DariYogyakarta, DI Yogyakartaglintsoffentliggjort 13.10.2026
Til stillingen
24 andre stillinger hos Staffinc Affiliate - Sri Wulan Dari →
Skal:PythonDockerDataQA/TestAI

di Staffinc Group.

📍 Lokasi: Kota Yogyakarta 💼 Tipe Pekerjaan: Kontrak 💰 Gaji: Rp 3.000.000 - Rp 5.000.000 🎁 Benefit: BPJS TK, BPJS Kesehatan, Tunjangan Hari Raya, Fasilitas Kerja

Deskripsi Pekerjaan

VoIP & SIP Engineering: Act as the primary technical Ops for GoAutoDial/Asterisk configuration. You will solve complex connectivity issues, including NAT traversal, RTP packet loss, and "one-way audio" troubleshooting. AI Pipeline Development: Build and maintain a voice-to-text pipeline using Whisper and Ollama (Phi-4/Hermes) on Apple Silicon (Mac Studio) to automate QA scorecards for up to 100+ agents. System Orchestration: Use n8n to create the "glue" between GoAutoDial recordings, Google Drive Shared Storage, and our internal reporting dashboards. Scripting & Integration: Write Python scripts to automate file management, audio transcoding (ffmpeg/sox), and API interactions between our BPO tools (Moodle, GLPI, Mattermost). Infrastructure Optimization: Collaborate with the Infrastructure Manager to optimize our Colocation server (Dell PowerEdge) for high-concurrency dialing and AI processing.

Persyaratan Pekerjaan

  1. Male/Female
  2. Age max 40
  3. Education : D3/S1
  4. Advanced VoIP Skills: Expert-level knowledge of SIP/RTP protocols. You must be comfortable using sngrep, tcpdump, or Wireshark to debug call signaling and audio streams.
  5. Linux System Engineering: Deep experience with Linux-based telephony (Asterisk/Vicidial/GoAutoDial) and containerization (Docker/Docker Compose).
  6. AI/LLM Experience: Familiarity with running local models via Ollama and integrating them into business workflows.
  7. Automation Mindset: Proven track record of building production-grade automations using n8n or similar tools.
  8. Problem Solver: Ability to diagnose and fix configuration-level bugs that traditional "Network/Hardware" teams might miss.

Skills: Deep Learning, Data Engineering, Machine Learning, Natural Language Processing (NLP), Artificial Intelligence, Neural Network, Data Mining, Pattern Recognition, Computer Vision, Redis