About the Company
Meta builds technologies that help people connect, find communities and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions of people around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution of social technology. We are constantly innovating our core platforms and pushing the boundaries of what’s possible with AI and machine learning to create more personalized and engaging experiences for our users across all our platforms.
Job Description
We are seeking a highly skilled Machine Learning Specialist with a dedicated focus on social media algorithms, particularly those akin to Pinterest’s recommendation engine. In this role, you will be instrumental in analyzing, optimizing, and developing cutting-edge machine learning models to enhance user experience and content discovery. You will work within our core AI research team, contributing to projects that directly impact how millions of users interact with visual content and discover new interests. This is an exciting opportunity for an ML expert passionate about recommendation systems, data-driven insights, and building the future of social technology.
Key Responsibilities
- Design, develop, and implement advanced machine learning models specifically for content recommendation and personalization, with a strong emphasis on visual discovery and user engagement.
- Analyze and interpret large datasets from social media platforms to identify patterns, trends, and opportunities for algorithm improvement.
- Optimize existing algorithms and develop new ones to enhance relevance, diversity, and freshness of recommended content.
- Collaborate closely with product managers, data scientists, and engineers to translate business requirements into technical specifications and deliver impactful ML solutions.
- Conduct A/B testing and experimentation to evaluate model performance and iterate on improvements.
- Stay abreast of the latest research and industry trends in machine learning, recommendation systems, and computer vision, especially concerning social media platforms.
- Prepare detailed technical documentation and presentations for internal stakeholders.
Required Skills
- Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong understanding of various machine learning algorithms, including deep learning, reinforcement learning, and traditional ML techniques.
- Extensive experience with recommendation systems, collaborative filtering, content-based filtering, and hybrid approaches.
- Solid foundation in statistics, probability, and linear algebra.
- Experience with large-scale data processing using tools like Spark, Hadoop, or similar distributed systems.
- Ability to analyze complex data, draw actionable insights, and communicate findings effectively.
- Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
Preferred Qualifications
- Master's or Ph.D. in Computer Science, Machine Learning, or a closely related field.
- Direct experience working with social media platform data and algorithms (e.g., Pinterest, Instagram, TikTok, YouTube).
- Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps practices.
- Experience with graph neural networks or knowledge graphs for recommendation.
- Publications in top-tier ML conferences (e.g., NeurIPS, ICML, KDD, WWW).
Perks & Benefits
- Comprehensive health, dental, and vision insurance for you and your family.
- Generous paid time off, including vacation, sick leave, and company holidays.
- Competitive salary, equity, and performance-based bonuses.
- Opportunities for professional development, including conferences, workshops, and internal training programs.
- Wellness programs, fitness memberships, and mental health support.
- On-site amenities, including cafeterias, fitness centers, and recreational areas.
- 401(k) matching and financial planning resources.
- Paid parental leave and family support benefits.
How to Apply
If you are interested in this position, please click the "Apply Now" button below. To ensure your application is properly considered, please prepare the following:
- An up-to-date Resume or CV
- A brief cover letter summarizing your experience and motivation
Applications are reviewed on a rolling basis. Only shortlisted candidates will be contacted for an interview.
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