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Machine Learning Scientist 6, Creative & Policy - Ads
Career Insights for Machine Learning Engineer
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What they do
A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
$168,439 / year median in California
Job Description
- Hire, inspire, and grow high-performing Machine Learning Scientists, Analytics Engineers, and Data Scientists.
- Lead strong partnerships with stakeholders from across the business - from product, engineering, to consumer insights, content, and strategy.
- Instill an inclusive culture that is innovative and collaborative, both within your team and in the broader organization.
- Develop a team charter and roadmap that optimizes the impact of the team and reflects evolving business needs.
- Act as an ambassador between the Product, Engineering, Strategy, and DSE teams by having a deep knowledge of how the Netflix Ads product works.
- Ensure that your team is producing consistently trustworthy and high-quality technical outputs that influence & impact the business. ## About You (Requirements)
- Demonstrated tenacity, resilience, and leadership experience that enables you to organize and drive cross-functional projects, overcome challenges, and propose solutions.
- Be both quantitative and qualitative. You should be able to quickly assess and understand complex systems, but also have high EQ, so that you can be a product ambassador to the rest of the organization.
- You are a player-coach. You can develop roadmaps and strategy, but also execute on technical work and ensure that your team produces consistent high quality outputs.
- Superb communication skills - You must be able to cultivate strong working relationships, communicate effectively, write meticulously, and give outstanding presentations to both technical and creative audiences.
- Experience working with multimodal LLMs, VLMs.
- Experience building and leading hybrid Analytics, Data and ML teams in the Ads space.
- Capacity and passion to translate business objectives into actionable analyses, and use analytics to guide product and business with quantitative recommendations.
- A passion for TV and movies and defining the future of entertainment.