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 rapid-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.

Skills:- Video Editing, Multi-modal AI, Computer Vision, Natural Language Processing (NLP), Python, PyTorch and TensorFlow

📌 Sr Video ML Engineer (Founding Team) (India)
🏢 Cliply Pte
📍 India