Staff Machine Learning Engineer (AI Platform)

What you'll do

• Build ML-based software systems for advertising experiences and campaigns
• Drive long-term technical architecture evolution of domain
• Be a role model for technical excellence
• Coach, mentor and train ML Engineering talent
• Work with diverse datasets including image, video, audio, text, and structured data
• Contribute to and strengthen MLOps and data platform
• Collaborate with senior ML engineers, data scientists, and software engineers
• Impact daily life of hundreds of advertisers using Smartly
• Work with stakeholders across product, engineering, and infrastructure
• Translate business/product needs to viable ML solutions
• Enhance soft skills through knowledge sharing, meetings, and pair programming
• Stay updated with latest ML innovations in generative AI, computer vision, NLP, and explainability

Requirements

• 8+ years of experience developing and deploying production-quality software
• 5+ years of experience delivering software services powered by machine learning
• 4+ years of experience working with cloud infrastructure such as AWS or GCP
• Fluent in Python; experience with C++ or Java is a plus
• Demonstrated experience managing the technical direction of a software system
• Experience in coaching and mentoring senior engineers
• Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Knowledge of MLOps concepts and tools (e.g., MLflow, Kubeflow)
• Experience in feature engineering, model evaluation, diagnostics, and monitoring
• Strong foundation in linear algebra, statistics, and calculus
• Experience building scalable data pipelines for ML-based data processing
• Experience developing and maintaining services under SLA
• Analytical mindset with a problem-solving approach
• Passion for solving customer challenges quickly while making thoughtful architectural decisions
• Adaptability and resilience when facing new or ambiguous challenges
• Strong written and verbal communication skills in English
• M.Sc. in a relevant field is preferred
• Ability and willingness to work in a hybrid capacity from our office 3 days a week

Tech stack

Benefits