Computer Vision Engineer

Selamat Datang di Situs Lowongan Kerja Indonesia Terbaru 2026 dan Saat ini kami ingin memberitahukan Info Terbaru Mengenai Informasi Loker dari Perusahaan McEasy dengan posisi Computer Vision Engineer. Untuk selengkapnya silahkan baca deskripsi lowongan kerja di bawah ini dengan seksama dan teliti, beserta persyaratan minimal lowongan kerja di yang telah tertera dan dijelaskan di bawah ini.

McEasy melalui program rekrutmennya saat ini sedang membuka lowongan kerja untuk posisi Computer Vision Engineer di Surabaya yang bertujuan untuk meningkatkan kinerja operasional di dalam maupun luar kantor McEasy. Perusahaan Tersebut sedang mencari calon tenaga kerja yang siap diterjunkan ke setiap divisi bagian perusahaan yang sesuai dengan posisi, kemampuan dan keahlian para pencari kerja tersebut. Berikut ini adalah detail lengkap persyaratan untuk posisi Computer Vision Engineer di Surabaya Perusahaan McEasy:

We are looking for a Senior Computer Vision / ML Engineer to own the AI that turns our dashcam and video feeds into a defensible product — the core of TrackVision and our driver-safety roadmap.

This role is about training real computer-vision models.

It is about turning raw video from tens of thousands of vehicles into accurate, real-time detection that runs cost-effectively at the edge — and shipping it to production.

You will work closely with leadership to:

• own the video-intelligence roadmap (fatigue, distraction, ADAS-style alerts, cargo & theft detection)
• train, optimize and deploy CV models that run on-vehicle / at the edge
• build the moat: capabilities a software-only competitor cannot copy

What will you do?

1. Own Video Intelligence

• Build and train CV models for driver fatigue & distraction detection, ADAS-style road & event detection, and cargo, theft, and in-cabin monitoring.
• Turn messy, real-world video into reliable detections.

2. Optimize for the Edge

• Make models run cost-effectively at scale using quantization, pruning, distillation, on-device/edge inference, and trigger-based, event-driven processing.
• Treat inference cost-per-camera as a first-class design constraint.

3. Train, Don’t Just Wrap

• Build custom models where they create differentiation.
• Use pre-trained backbones and transfer learning to move fast.
• Know when to fine-tune vs. build from scratch.

4. Own the Vision Data Pipeline

• Define annotation specs and quality standards (labeling is outsourced — you own the spec).
• Build training and evaluation datasets from real fleet video.
• Monitor model drift and retrain as conditions change.

5. Ship to Production

• Deploy models into the product, not notebooks.
• Build inference services (edge + cloud), monitoring, and versioning.
• Iterate from real field performance.

6. Collaborate Across Teams

• Work with Hardware/IoT Engineers on dashcams and edge devices.
• Partner with Data & AI Product Engineers for shared data and benchmarking.
• Collaborate with Software Engineers and Product/Leadership to integrate solutions and refine use cases.

Qualifications:

Must-Have

• Strong computer-vision and deep-learning fundamentals (object detection, image/video models)
• Hands-on with PyTorch or TensorFlow — training, not just inference
• Track record deploying CV models to production (real users, real data — not just papers or Kaggle)
• Experience optimizing models for real-time / resource-constrained inference
• Solid engineering (Python; can build and ship services)
• Comfort with messy, real-world image/video data at scale

Nice-to-Have

• Edge / embedded deployment (NVIDIA Jetson, mobile, on-device, TensorRT/ONNX)
• Driver monitoring / ADAS / dashcam / automotive vision experience
• Data-centric ML and annotation-pipeline design
• Inference cost optimization at fleet scale
• MLOps: model versioning, monitoring, automated retraining

Ready to embark on a thrilling journey with us? If you’re eager to bring your passion, energy, and expertise to our dynamic team, simply click ‘Easy Apply‘ and let the adventure begin! Your next career move is just one click away – let’s make it happen together!