Machine Learning Scientist
Confirmed on the employer's own hiring board on Oct 8, 2026. First seen by Alion on Jul 2, 2026.
Join our team as a Machine Learning Scientist, where you'll leverage your expertise in building and deploying production machine learning models to create real value for YouTube creators. You'll work in a fast-paced startup environment, training, evaluating, optimizing, and deploying a wide range of machine learning models. Your passion for AI and machine learning will drive you to stay at the forefront of the field and continuously improve our products.
Missions
- Designing, training, evaluating, optimizing, and deploying production machine learning models, particularly in areas such as deep learning, reinforcement learning, and recommendation systems.
- Building recommendation, ranking, and personalization systems that adapt to creator behavior, product feedback, and changing objectives.
- Collaborating closely with Product and Engineering to translate customer problems into machine learning solutions, and staying current with advances in AI and machine learning.
Profil recherché
- Curiosity, ownership, and a passion for building products that customers love- Experience training, evaluating, tuning, and deploying machine learning models across deep learning and traditional ML approaches
- Experience with offline evaluation, A/B testing, counterfactual reasoning, causal inference, or other methods for measuring model impact
- Reinforcement learning systems
- Excellent communication skills and the ability to work cross-functionally with Product, Engineering, Analytics, and other stakeholders
- Strong understanding of embeddings, representation learning, neural networks, sequence modeling, and modern deep learning architectures
- Strong experience with modern deep learning frameworks and production ML workflows
- Strong understanding of reinforcement learning concepts such as exploration vs. exploitation, reward design, policy evaluation, delayed feedback, feedback loops, and sequential decision-making
- Recommendation systems
- Experience designing experiments and using data to improve model performance in real-world product environments
- Strong Python and SQL skills
- Contextual bandits
- Adaptive decision-making systems
- Online learning systems
- 5+ years building, evaluating, and deploying machine learning models in production environments
- Personalization models
- Ranking systems
- Experience building one or more of the following:
- Experience working with logged interaction data, behavioral data, or feedback signals to train, evaluate, and improve models
- Master’s degree or PhD in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or another quantitative field
- Experience with large-scale recommendation, ranking, personalization, or adaptive optimization systems
- Familiarity with ad recommendation, ad ranking, or campaign optimization systems used by large-scale platforms, such as YouTube, Google, Meta, TikTok, Amazon, or similar consumer marketplace platforms
- Experience serving large-scale ML models in production
- Experience building machine learning systems for large-scale digital platforms, such as creator platforms, consumer apps, recommendation systems, ad recommendation systems, campaign optimization systems, or workflow automation tools