ML Engineer L5 - Ads Platform Engineering (Forecasting)

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Written by AI from the job title and company, not by Netflix, so some details may not match this job. The employer's own page has the real description.

Overview

The Machine Learning Engineer L5 - Ads Platform Engineering (Forecasting) at Netflix will play a pivotal role in enhancing our advertising platform by developing sophisticated machine learning models that drive predictive analytics and optimize campaign performance. The candidate will leverage their expertise in data science and machine learning to innovate and improve forecasting models, harnessing extensive datasets to yield actionable insights. Collaboration with cross-functional teams will be key in delivering high-quality, efficient solutions that impact our advertising strategies and contribute to overall business objectives.

Job Responsibilities

• Design and implement robust machine learning algorithms for forecasting and performance optimization of ad campaigns.
• Collaborate with data scientists and product teams to gather requirements and ensure that solutions are aligned with business goals.
• Analyze large datasets to extract insights and refine predictive models, enhancing accuracy and performance.
• Monitor and maintain machine learning models in production, ensuring reliability and continuous improvement.
• Provide expertise in selecting appropriate statistical methods and modeling techniques to address complex forecasting challenges.
• Communicate findings and recommendations to stakeholders through effective presentations and reports.
• Stay current with industry trends and advancements in machine learning to innovate and incorporate new techniques into existing models.

Qualifications

• Bachelor's or master’s degree in Computer Science, Data Science, Mathematics, or a related field.
• 5+ years of experience in machine learning engineering or a related area, preferably within advertising or digital marketing.
• Proficiency in programming languages such as Python, Scala, or Java with solid experience in data manipulation libraries.
• Strong understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and statistical analysis techniques.
• Experience with distributed computing tools (e.g., Apache Spark) and databases (e.g., SQL, NoSQL) for handling large-scale datasets.
• Strong analytical skills with the ability to translate complex data into actionable insights.
• Excellent communication and interpersonal skills, enabling effective collaboration with diverse teams.

Technologies & Tools

The Machine Learning Engineer will utilize various technologies and tools including Python, TensorFlow, PyTorch, Apache Spark, and SQL databases. Familiarity with cloud platforms such as AWS or Google Cloud is also essential for deploying and scaling machine learning models. The role involves working with version control systems like Git and collaboration tools such as JIRA to manage projects effectively.

Ideal Candidates

Ideal candidates will demonstrate a strong passion for machine learning and data-driven decision-making. They will possess a solutions-oriented mindset, showcasing creativity and innovation in solving problems in a fast-paced environment. Excellent teamwork and collaboration skills are essential, along with a proactive approach to stay ahead of industry trends. A desire for continuous improvement and a commitment to delivering impactful results will further distinguish the successful candidate in this role.