Meta - Los Angeles, CA
posted 2 months ago
Meta is seeking Machine Learning Engineers to join our engineering team, specifically in the role of Software Engineer (Technical Leadership) - Machine Learning. The ideal candidate will have industry experience working on a range of classification and optimization problems such as payment fraud detection, click-through rate prediction, click-fraud detection, search ranking, text/sentiment classification, collaborative filtering/recommendation, or spam detection. This position will involve leveraging these skills to tackle some of the most exciting and massive social data and prediction problems that exist on the web. In this role, you will drive the team's goals and technical direction, pursuing opportunities that enhance the efficiency of the larger organization. You will be responsible for effectively communicating complex features and systems in detail, understanding industry and company-wide trends to assess and develop new technologies. Collaboration is key, as you will partner with organization leaders to improve the performance of the team and the organization as a whole. You will also identify new opportunities for the larger organization and influence the appropriate stakeholders for staffing and prioritizing these new ideas. Your responsibilities will include suggesting, collecting, and synthesizing requirements to create an effective feature roadmap, as well as developing highly scalable classifiers and tools that leverage machine learning, data regression, and rules-based models. You will adapt standard machine learning methods to best exploit modern parallel environments, such as distributed clusters, multicore SMP, and GPU. This position requires a strong technical background and a proven track record in leading projects with industry-wide impact, mentoring senior engineers, and planning multi-year roadmaps that align short-term projects with long-term vision. You will be expected to drive large cross-functional engineering efforts, making this a pivotal role within the organization.