Senior AI / Machine Learning Engineer

Job Summary Senior AI / Machine Learning Engineer will build, train, and optimize machine learning models for content understanding, ranking, and scoring. You will transform research concepts into robust, production-ready ML pipelines and maintain high-quality code to drive impactful AI solutions. Responsibilities

• Implement deep learning models for video, image, audio, or text using modern frameworks to enhance content understanding and ranking capabilities

• Develop and maintain training and evaluation pipelines, including data loaders, augmentations, and metrics, to ensure reliable model performance

• Design and execute experiments, tune hyperparameters, and optimize models for latency and accuracy to meet production requirements

• Collaborate with backend engineers to deploy models via scalable APIs and services, enabling seamless integration into production systems

• Monitor model performance in production environments and design retraining and improvement loops to sustain and enhance model effectiveness

• Contribute to the development of ML tooling, experiment tracking systems, and comprehensive documentation to support team productivity and knowledge sharing

Required competencies and certifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field

• 4–7+ years of experience as an ML Engineer, Applied Scientist, or equivalent role

• Proficiency in PyTorch or TensorFlow and common machine learning libraries to develop and optimize models

• Experience in at least one domain: computer vision, video processing, speech/audio processing, or natural language processing (NLP)

• Strong understanding of model optimization techniques such as quantization, pruning, distillation, and batching to improve model efficiency

• Familiarity with GPU training, distributed training, and cloud-based ML workflows to support scalable model development

• Strong coding skills in Python and solid grasp of software engineering best practices to produce maintainable and efficient code

Preferred competencies and qualifications

• Master’s degree in Machine Learning, Artificial Intelligence, Data Science, or related field preferred but not mandatory with sufficient experience

• Experience with MLOps tooling such as MLflow or Weights & Biases (W&B) to streamline model lifecycle management

• Background in Kaggle competitions or similar machine learning contests demonstrating practical problem-solving skills

• Prior experience working in startup environments, contributing to fast-paced and innovative projects

IMPORTANT NOTE: Please apply only if you have hands‑on experience with video machine learning. This role requires expertise in:

• video transformers (e.g., VideoMAE, TimeSformer, ViViT, SlowFast)

• temporal modelling and spatiotemporal architectures

• multimodal fusion (video + audio + text)

• GPU‑optimised inference (TensorRT, ONNX, CUDA)

• training and deploying production‑grade video or multimodal models

Candidates focused mainly on classical CV (YOLO/OCR), data science/analytics, LLM application development, or MLOps/pipeline engineering will not be a match for this role.