Machine Learning Engineer – Staff, Principal

🕒 April 8

🏢🏡 San Francisco – Hybrid

💵 $239k - $342k / year

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

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Tubi

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2014

📱 Media

Media • Entertainment • Advertising

Tubi is a free, ad-supported streaming service offering a wide selection of movies and TV shows. It features a diverse array of content categories including comedy, romance, drama, horror, and action. Tubi provides a platform for both classic and contemporary films, appealing to a wide audience by keeping its service free and easily accessible across various devices. With a focus on providing entertainment without subscription fees, Tubi partners with other businesses for personalized advertising and viewer engagement.

📋 Description

• 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

• 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

• medical/dental/vision insurance • 401(k) plan • paid time off • annual discretionary bonus • long-term incentive plan • wellness reimbursement