Video AI Engineer: Gen AI, CV, and MLOps (Remote)

Instavar; Singapore; Hybrid; SGD 140,000 - 210,000; Full time

Benefits offered by this job

Equity package

Health, dental, vision insurance

Flexible work arrangements (remote/hyb

Conference attendance opportunities

Publish and present research

Job summary

Instavar is hiring a senior ML Engineer in Singapore to lead end-to-end video generation, processing, and analysis models. You will develop and test models that meet real product needs, then optimize production performance across latency, accuracy, and reliability.

You will also shape the data and evaluation systems to train, compare, monitor, and run models, collaborating with product and engineering teams in a fast-paced startup environment.

Qualifications

• 3+ years of experience in machine learning and AI.
• PhD in CS/AI or related field.
• Experience with generative AI models (GANs, VAEs, Diffusion).
• Knowledge of video codecs and streaming technologies.
• Experience with cloud platforms (AWS, GCP, or Azure).
• Understanding of MLOps and model deployment.

Responsibilities

• Build and test models for video generation, processing, and analysis, then test them against real product needs.
• Improve production behaviour by making models faster, more accurate, and reliable under practical constraints.
• Build the evidence pipeline: create data and evaluation systems needed to train, compare, monitor, and run models.

Skills

Python

TensorFlow

PyTorch

Computer vision

Video processing

CNNs

RNNs

Transformers

AWS

MLOps

Model deployment

Distributed training

Edge deployment

Video codecs

Research publication

Education

PhD in Computer Science, AI, or related field

Job description

Instavar is hiring a senior ML Engineer in Singapore to lead end-to-end video generation, processing, and analysis models. You will develop and test models that meet real product needs, then optimize production performance across latency, accuracy, and reliability.

You will also shape the data and evaluation systems to train, compare, monitor, and run models, collaborating with product and engineering teams in a fast-paced startup environment.