About the Company
Snap Inc. is a camera company. We believe that reinventing the camera represents our greatest opportunity to improve the way people live and communicate. Our products empower people to express themselves, live in the moment, learn about the world, and have fun together. We are constantly innovating to build new ways for our community to engage with augmented reality, creative tools, and powerful content recommendations.
Job Description
We are seeking an innovative and data-driven Machine Learning Specialist with a strong interest in recommendation systems and content discovery algorithms, particularly those akin to Pinterest’s. In this role, you will be instrumental in developing, deploying, and optimizing sophisticated machine learning models to enhance user experience, content engagement, and personalization across our platforms. You will work within a dynamic team, transforming raw data into actionable insights and robust ML solutions that drive our product forward. Your focus will be on understanding user preferences, predicting engagement patterns, and delivering highly relevant content through cutting-edge algorithmic design and implementation.
Key Responsibilities
- Design, develop, and implement advanced machine learning models for content recommendation, search, and personalization, with an emphasis on discovery mechanisms similar to Pinterest's.
- Analyze large datasets to identify trends, patterns, and insights that inform algorithmic improvements and new feature development.
- Collaborate with product managers, data scientists, and engineers to translate business requirements into technical specifications and deliver high-impact ML solutions.
- Perform A/B testing and experimentation to validate model performance and measure the impact of algorithmic changes on key user metrics.
- Optimize existing ML models for performance, scalability, and efficiency in a production environment.
- Stay abreast of the latest advancements in machine learning, particularly in recommendation systems, and integrate new techniques and technologies as appropriate.
- Contribute to the team's best practices for code quality, model reproducibility, and deployment pipelines.
Required Skills
- 5+ years of experience in Machine Learning, Data Science, or a related field.
- Strong proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Extensive experience with recommendation systems, ranking algorithms, and content personalization.
- Solid understanding of statistical modeling, experimental design, and A/B testing methodologies.
- Proficiency in SQL and experience working with large-scale datasets.
- Experience with cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Hadoop).
- Excellent problem-solving skills and the ability to work independently and as part of a team.
Preferred Qualifications
- Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- Experience working on consumer-facing products with millions of daily active users.
- Familiarity with graph neural networks or other advanced techniques for relationship modeling.
- Previous experience optimizing algorithms for visual content discovery platforms.
- Understanding of MLOps principles and practices for deploying and managing ML models in production.
Perks & Benefits
- Competitive salary and equity package
- Comprehensive health, dental, and vision insurance
- Paid time off and company holidays
- 401(k) matching program
- Generous parental leave policy
- Professional development opportunities and conference attendance
- On-site fitness centers, wellness programs, and healthy snacks/meals (where applicable for hybrid roles)
- Employee assistance program
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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