Cliply Pte Ltd

Role Overview

The Senior AI/ Machine Learning Engineer will design, build, and optimise the core intelligence layer that powers Cliply’s video understanding and content analysis platform.

This role blends deep hands-on engineering with architectural ownership. You will work across video, audio, and text modalities, shaping model design while also delivering production-ready ML systems. You will be the technical anchor for Cliply’s AI stack, partnering closely with the Lead Architect and the engineering team to bring research concepts into scalable, real-world systems.

Key Responsibilities

Multimodal & Video ML Architecture

• Design and validate deep learning architectures for video, audio, and text understanding, including temporal modelling and multimodal fusion.
• Define approaches for long-sequence modelling, representation learning, and sequence-to-sequence tasks.
• Lead experiments with transformers, vision transformers, video encoders, and hybrid multimodal architectures.

Model Development & Optimisation

• Build and optimise models for content understanding, highlight detection, ranking, and scoring.
• Implement training pipelines, data loaders, augmentations, and evaluation metrics for large-scale video datasets.
• Optimize models for latency, throughput, and GPU efficiency using techniques such as quantization, pruning, distillation, batching, and ONNX/TensorRT.

Production ML Engineering

• Convert prototypes into robust, production-ready services.
• Collaborate with backend engineers to deploy models via scalable APIs and micro-services.
• Monitor model performance in production and design retraining loops for continuous improvement.

Technical Leadership

• Establish best practices for experimentation, evaluation, documentation, and reproducibility.
• Provide mentorship to junior engineers and contribute to Cliply’s long-term AI roadmap.
• Influence architectural decisions across the AI stack to ensure scalability and reliability.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
• 5–10+ years of experience as an ML Engineer, Applied Scientist, or similar role.
• Strong proficiency in PyTorch or TensorFlow, with hands-on experience training deep learning models.
• Deep expertise in multimodal video machine learning,
• Expertise in at least two of the following:

1. Video understanding / video ML
2. Computer vision
3. Speech/audio processing
4. Natural language processing
5. Multimodal fusion

• Experience with GPU training, distributed training, and large-scale datasets.
• Strong understanding of model optimization (quantization, pruning, distillation, ONNX/TensorRT).
• Solid software engineering fundamentals (Python, version control, testing, code review).

Preferred Qualifications

• Experience with multimodal architectures (video-text, audio-text, cross-modal transformers).
• Experience with MLOps tooling (MLflow, Weights & Biases).
• Prior work in startup environments or fast-paced product teams.
• Contributions to open-source ML projects or competitive ML experience (e.g., Kaggle).

Why Join Cliply

• Build the core intelligence layer of a next-generation video understanding platform.
• Own end-to-end architecture and model design - your work becomes the product.
• Work with a founder-led team that values technical excellence, autonomy, and speed.
• Shape the future of multimodal AI in a real product used by creators and enterprises.