Senior Machine Learning Engineer
1 week ago
Our Roku-branded TVs, Roku TV models, Smart Home system, streaming players, audio equipment, and the purpose-built operating system that powers it all can turn any home into a home theater, with seamless integration of hardware and software.
Our commitment to our users extends to our brand studio, which creates innovative Roku Originals exclusively for The Roku Channel, a free channel that reaches approximately 80 million households in the U.S and Mexico.
Join us, and you'll have the chance to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines.
Job Description :
The person in this role will leverage their leadership and technical skills, business intuition, and analytical thinking to build best-of-class machine learning products.
Hence, communication and presentation skills are essential. The role requires high technical aptitude, problem-solving abilities, motivation, and exceptional attention to detail.
We're always in build mode because we're a company of data-focused builders, especially on the data-driven team. Every day, you'll look at what exists and find ways to improve it.
Responsibilities:
- You will be responsible for hiring and developing a team of exceptional Software and ML engineers who build and own the next generation of content recommendations and other algorithms/systems to make the experience for millions of Roku users 100% personalized and unique.
- Partner with senior stakeholders to plan and drive the ML strategy for the personalization experience.
Requirements:
years of relevant Machine Learning Management experience in a fast-growing public company.
- Strong CS fundamentals.
- Should be able to write an algorithm with ease.
- Good understanding of data science and machine learning fundamentals like regression, classification, tree-based approach, neural networks, sequence-based approaches, and NLP approaches like W2V or Bert
- Can brainstorm and identify the right KPIs and objective functions.
- Experience building in-production recommendation systems.
- Good understanding of system architecture.
- Experience in big data technologies - streaming architecture, data pipelines (Spark, EMR, S3 Airflow).
- Bachelor's in computer science, Statistics, or related field, but a Ph.D or Masters in CS or related fields is preferred
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