ML Engineer

Responsibilities:
Design, build, and maintain ML systems that power the dubbing platform.
Develop automated validation and monitoring mechanisms to ensure consistent system behaviour.
Optimise model inference pipelines for performance, cost, and reliability.
Build data and evaluation workflows to support continuous improvement.
Run experiments and validate changes before production rollout.
Collaborate with product, engineering, and operations teams to deliver high-quality features.
Document systems, workflows, and best practices.
Requirements:
Strong foundation in machine learning and deep learning.
3-6 years of relevant industry experience in ML/AI.
Experience deploying ML systems in production environments.
Proficiency in Python and modern ML frameworks (e. g., PyTorch).
Solid understanding of model optimisation, debugging, and performance tuning.
Experience working with GPU-based workloads.
Bonus Points:
Experience with speech, audio, or multimodal systems.
Familiarity with large-scale ML infrastructure and cloud platforms.
Exposure to distributed systems, containers, and orchestration tools.
Experience building evaluation frameworks for ML systems.

Experience
3-6 yrs