About the Company
Meta Platforms is a global technology leader connecting billions of people worldwide. We are at the forefront of innovation, building technologies that help people find communities, grow businesses, and explore new frontiers. Our work spans across social media, virtual reality, augmented reality, and cutting-edge artificial intelligence research. We foster a culture of bold thinking, collaboration, and impact, empowering our employees to tackle some of the world’s most complex technical challenges.
Job Description
We are seeking a highly motivated and skilled Machine Learning Specialist with a particular focus on algorithm analysis and development, specifically relating to social media platforms like Pinterest. In this role, you will be instrumental in understanding, reverse-engineering, and optimizing recommendation and ranking algorithms to enhance user engagement, content discovery, and overall platform performance. You will work within a dynamic team of engineers and data scientists, contributing to strategic initiatives that push the boundaries of machine learning applications in a high-impact environment. This position requires a deep understanding of ML principles, strong programming skills, and a keen analytical mind to dissect complex systems.
Key Responsibilities
- Analyze and deconstruct existing recommendation and ranking algorithms used by major social media platforms, with a specific emphasis on Pinterest's ecosystem.
- Design, develop, and implement novel machine learning models and algorithms to improve content discovery, user engagement, and personalization.
- Conduct extensive data analysis to identify trends, patterns, and insights from large-scale datasets relevant to user behavior and algorithm performance.
- Collaborate with cross-functional teams, including product managers, engineers, and researchers, to define project scope and deliver high-impact solutions.
- Develop and maintain robust, scalable machine learning pipelines and infrastructure.
- Evaluate and benchmark the performance of various algorithms using rigorous A/B testing and other statistical methods.
- Stay abreast of the latest advancements in machine learning, deep learning, and artificial intelligence, particularly in the domain of social network analysis and recommendation systems.
Required Skills
- Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong understanding of machine learning algorithms, including supervised, unsupervised, and reinforcement learning.
- Experience with large-scale data processing technologies (e.g., Spark, Hadoop).
- Solid foundation in statistics, linear algebra, and calculus.
- Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and MLOps practices.
- Excellent problem-solving, analytical, and communication skills.
- Demonstrated ability to work with complex, real-world datasets.
Preferred Qualifications
- Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- Experience in analyzing or developing algorithms for social media, e-commerce, or content recommendation platforms.
- Knowledge of graph neural networks and their applications.
- Experience with distributed systems and high-performance computing.
- Publications in top-tier machine learning conferences (e.g., NeurIPS, ICML, KDD).
Perks & Benefits
- Comprehensive health, dental, and vision insurance.
- Generous paid time off and flexible work arrangements.
- 401(k) retirement plan with company match.
- Paid parental leave.
- Wellness programs and fitness reimbursements.
- On-site amenities (where applicable) including cafeterias, gyms, and shuttle services.
- Professional development opportunities and tuition reimbursement.
- Employee stock purchase plan.
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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