CHIEF AI ENGINEER

About the Role

Key Responsibilities

• Work closely with product managers and engineers to align on business goals, define machine learning challenges, and design effective ML solutions.
• Develop and deploy machine learning models, including building data pipelines, orchestrating ML workflows, and optimizing system performance and reliability.
• Maintain a robust codebase by writing well-tested code, covering both functional and non-functional aspects such as unit, integration, and load testing.
• Stay informed on industry trends and advancements in deep learning, experiment with new model concepts, and run both offline and online evaluations.
• Actively share knowledge through internal presentations, tech talks, and by promoting best practices in engineering and technology use.

Requirements

• Advanced degree (Master's or PhD) in Computer Science, Machine Learning or a related field.
• Over 10 years of hands-on experience developing and deploying production-ready machine learning systems, covering the full model lifecycle-training, tuning, deployment, serving, and monitoring.
• Experience with advertising technologies such as real-time bidding, auction models, dynamic pricing, recommendation engines, multi-armed bandits, and causal inference techniques is preferred.
• Expertise in cloud infrastructure (especially AWS), machine learning orchestration tools like Kubeflow, TensorFlow, and the use of Feature Stores in live environments.
• Experience scaling out MLE teams as tech lead or manager is preferred.
• Commercial experience with big tech companies and scaling startups is a plus.

Nice to Have

• Experience in advertising with real-time bidding, auction models, dynamic pricing, recommendation engines, multi-armed bandits, and causal inference techniques.
• Experience scaling out MLE teams as tech lead or manager.

Benefits & Perks

• The compensation package contains a base salary, a bonus, and a comprehensive benefits package.