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Machine Learning Engineer – Staff, Principal
TubiStaff Machine Learning Engineer contributing to video personalization projects at Tubi. Designing and implementing advanced algorithms while collaborating with cross-functional teams.
Tech Stack
Tools & technologiesPyTorchTensorflow
About the role
Key responsibilities & impact- Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience
- Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas
- Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment
- Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences.
- Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement
Requirements
What you’ll need- 8+ years of industry experience building production Machine Learning systems
- MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field
- Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks
- Proficiency in building and deploying full-stack machine learning pipelines: data extraction, data mining, model training, feature development, testing, and deployment.
- Solid understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning.
- Ability to deep dive into individual components and systems, as well as understand the overall architecture of machine learning solutions.
Benefits
Comp & perks- Medical/dental/vision
- Insurance
- Vacation/paid time off
- Annual discretionary bonus
- Long-term incentive plan
- Flexible Time Off Policy
- Generous Parental Leave Program
- Monthly wellness reimbursement