Software Engineer at Meta

Bellevue, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

10 Jan, 26

Salary

0.0

Posted On

12 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Econometrics, Statistical Modeling, Large Language Models, Causal Inference, Programming, Data Analysis, Visualization, Cloud Infrastructure, Software Development, Generative AI, Natural Language Processing, Computer Vision, Recommendation Systems, Collaboration, Communication

Industry

Software Development

Description

Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page. Responsibilities Design and develop cutting-edge Generative AI-powered tools for advertisers, leveraging advanced machine learning models, Large Language Models (LLMs), and econometric techniques to drive business growth and innovation. Collaborate with cross-functional teams to integrate Generative AI solutions into existing advertising platforms, ensuring seamless user experiences and optimal performance. Develop and maintain reliable, efficient, and scalable backend computing architectures and models to power Generative AI tools, utilizing expertise in system design, data analysis, and causal inference. Ensure the security, integrity, and compliance of all systems and data, adhering to Meta's high standards for data protection and privacy. Enhance ranking algorithms for fairness, personalization, and Small and Medium-sized Businesses (SMBs) empowerment, using econometric theory, machine learning methods, and data analysis to optimize algorithmic performance. Conduct research and experimentation to identify areas for improvement and develop innovative solutions to complex problems. Design and conduct experiments to analyze advertiser user behavior, identifying key business needs and decision-making patterns using causal inference, machine learning, and econometric techniques. Contribute to knowledge development by presenting findings and sharing insights with internal stakeholders and the broader academic community. Apply advanced data analysis and machine learning techniques to large datasets, extracting insights and developing predictive models that inform business decisions and drive growth. Utilize LLMs, natural language processing (NLP), and computer vision to analyze and generate content, optimizing advertising campaigns and improving user engagement. Design and develop recommendation systems that leverage Generative AI, machine learning, and collaborative filtering to provide personalized advertising experiences for users. Integrate GenAI-powered recommendation systems with existing advertising platforms, ensuring seamless user experiences and optimal performance. Continuously evaluate and refine recommendation systems to ensure they meet evolving user needs and preferences. Collaborate with cross-functional teams, including product management, design, and engineering, to ensure the successful development and deployment of Generative AI-powered tools and systems. Communicate complex technical concepts and research findings to non-technical stakeholders, providing clear and actionable insights that inform business decisions. Qualifications Ph.D. (or foreign degree equivalent) in Information Technology Management, Computer Science, Economics, Statistics, or a related field, and 6 months of experience in the job offered or in a computer-related occupation Experience must include 6 months of experience in the following: Machine learning,econometrics, and statistical modeling Large language model development and implementation Causal inference techniques,including instrumental variables,regression discontinuity, and difference-in-differences Programming in Hack, Python, Java, C++, R, and Julia Machine learning frameworks, including Tensor Flow and PyTorch Generative AI technologies, including GANs, VAEs,and LLMs Data analysis and visualization using pandas, NumPy,and Matplotlib Cloud infrastructure environments, including AWS and Google Cloud Platform Software development principles, including design patterns, testing methodologies, and version control systems

Responsibilities

Design and develop Generative AI-powered tools for advertisers, collaborating with cross-functional teams to integrate solutions into existing platforms. Conduct research and experimentation to enhance algorithms and optimize user experiences.