💼 AI Engineer
Perusahaan: McEasy | Sumber: LinkedIn | Tanggal Melamar: 2026-08-06
Status:Closed / No Response| Fit Score: Stretch | Rate Diusulkan: -
Tautan Pekerjaan: https://www.linkedin.com/jobs/view/4437010768/
📌 Detail Lamaran & Strategi Proyek
- Portofolio yang Ditunjukkan: None yet
- Connects Digunakan:
- Boosted: Tidak
📝 Catatan Mendalam, Wawancara & Pertanyaan Form
DECIDED NOT TO APPLY (Aug 6). Logistics/IoT SaaS. Remote, Indonesia, full-time.
GAP ANALYSIS vs must-haves: strong backend Python/Node = PARTIAL (Node/Express yes, Python no). Solid SQL and data manipulation = WEAK (Supabase/Postgres CRUD, not analytical SQL). Real-world messy datasets = NONE. Translate business problems to technical solutions = STRONG. Track record shipping features not prototypes = STRONG. Roughly 2.5 out of 5.
KEY INSIGHT: this is a DATA ENGINEERING job with an LLM wrapper. Core work is anomaly detection on fuel/trip/driver-behaviour telemetry, fleet benchmarking, and automated insights over 8+ years of IoT data using rules, thresholds and statistical methods. The AI part is one bullet out of five and it is the easy one (‘use LLMs for summarizing insights’). Portfolio has zero analytics, statistics, or time-series work.
UNLOCK: build one small anomaly-detection project over a public time-series dataset, deployed, with a write-up. That single artifact moves the profile from 2.5/5 to about 4/5 and opens the whole data-flavoured AI role category, which is a large share of the Indonesian remote market.
Also: reposted with 100+ applicants, meaning round one did not fill.