Machine Learning Engineer - Content Management & Distribution [Remote]
Machine Learning Engineer (L5) - Content Management & Distribution The goal of our Content Management & Distribution Data Science and Engineering team is to enable operational and creative excellence in the distribution and promotion of our content on our service. We collaborate closely with our partners in the Product Discovery & Promotion organization, and our work directly contributes to launching high-quality content on our service and helps our members discover content they will love. We conduct analyses, build analytical tools, and develop models to help our partners execute on these primary objectives. We are looking for a talented machine learning engineer to join our Merchandising & Content Understanding pod, which focuses on deepening our content metadata across all formats and improving the discovery experience on our service. You will design and develop models and infrastructure for algorithms that will power the next generation of capabilities for our business. You will partner with our world-class team of creative production practitioners and various cross-functional teams to shape strategy and deliver impact via machine learning and artificial intelligence solutions. Interested? Read more about the job description and qualifications below! What you will do:
- Collaborate closely with stakeholders in Product Discovery & Promotion to learn deeply about content metadata and merchandising and identify potentially impactful problems to solve via scalable machine learning and artificial intelligence solutions
- Develop innovative systems and models that empower decision-making for stakeholders and product features that can deliver member joy by leveraging a wide variety of metadata and production media generated by and collected from our productions throughout their end-to-end lifecycle
- Collaborate with team members and cross-functional partners to operationalize your models so that they can be integrated seamlessly into operational workflows
- Serve as a key thought partner for stakeholders, cross-functional partners, and our diverse set of team members regarding machine learning algorithms and system architectures
Your background and characteristics:
- Ph.D. or MS degree in a quantitative or computational field
- 4+ years of full-time work experience in one or more relevant machine-learning roles
- Practical experience in supervised, unsupervised, and deep machine learning methods
- Practical experience applying machine learning and Gen AI solutions to video, audio, and/or textual data sources
- Practical experience operationalizing or productionizing machine learning and/or artificial intelligence solutions
- Comfortable and effective in ambiguous problem spaces; ability to own and drive projects with minimal oversight and process
- Exceptional written and oral co mmunication with technical and non-technical audiences
Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $150,000 - $750,000 . Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled. Note: Posting is subject to change so please refer to career site for latest availability (SBJ-G337). Apply tot his job Apply To this Job