Principal Machine Learning Engineer, Ad Ranking
Job Title: Principal Machine Learning Engineer, Ad Ranking
Location: Hybrid
Company: Snapchat
Industry: Machine Learning, Advertising Technology, AI
About the Role:
Are you a visionary in machine learning, eager to revolutionize digital advertising? As the Principal Machine Learning Engineer for Ad Ranking at [Company Name], you'll lead the charge in designing and developing advanced ML models that power personalized, high-impact advertising experiences. This role offers a unique opportunity to combine deep technical expertise with strategic thinking to optimize ad relevance, engagement, and monetization at scale.
In this leadership role, you will collaborate with cross-functional teams to create innovative ranking algorithms that influence the future of digital advertising. Your work will directly shape how users experience advertisements across various platforms, driving both user satisfaction and business growth. If you're excited about building machine learning systems that make a real-world impact, this is the place for you!
What You’ll Do:
- Lead Machine Learning Innovation: Design and implement state-of-the-art ML models for ad ranking that optimize user experiences while maximizing ad effectiveness and revenue.
- Drive Technical Strategy: Define and execute the technical vision for ad ranking systems, ensuring the integration of cutting-edge algorithms and the alignment of ML models with business goals.
- Collaborate with Cross-Functional Teams: Work closely with product managers, engineers, data scientists, and designers to integrate ML models into real-time ad-serving systems, ensuring robust performance across platforms.
- Optimize Ad Systems: Continuously refine ad ranking algorithms by leveraging large datasets, A/B testing, and experimentation to improve ad relevance and performance.
- Scale and Deploy Models: Ensure that models are scalable, efficient, and capable of running in real-time production environments, delivering seamless user experiences at massive scale.
- Mentor and Lead a Team: Guide and mentor junior and mid-level engineers, fostering a culture of innovation, continuous learning, and high-quality software development.
- Contribute to the AI Community: Share insights by publishing papers, contributing to conferences, and participating in knowledge-sharing sessions within and outside the company.
What We’re Looking For:
- 7+ years of experience in machine learning, with a proven track record of building and deploying production-level ML models in real-world applications.
- Expertise in ad ranking systems, recommendation engines, or personalization algorithms, with a strong understanding of how machine learning can be applied to digital advertising.
- Deep knowledge of supervised learning, reinforcement learning, and deep learning techniques, particularly in ranking, optimization, and user behavior prediction.
- Proficiency in programming languages such as Python, Java, or C++, and hands-on experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
- A strong foundation in big data technologies and experience working with large-scale data systems, such as Hadoop, Spark, or Kafka.
- Experience with A/B testing, data experimentation, and other model evaluation techniques used to optimize ad performance.
- Ability to think critically about business challenges and translate them into innovative ML solutions that drive tangible results.
- Strong leadership and communication skills, with the ability to collaborate across teams and articulate complex technical concepts to non-technical stakeholders.
Bonus Points:
- PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field with a focus on ad tech or ranking systems.
- Experience with cloud platforms like AWS, Google Cloud, or Azure, and knowledge of deploying and maintaining ML models at scale.
- Familiarity with advertising ecosystems and understanding of the dynamics between users, ads, and businesses in digital platforms.
- Contributions to the ML/AI community, such as open-source projects, publications, or conference presentations.
- Experience with reinforcement learning or multi-arm bandit algorithms applied to ad ranking.
Why Snapchat?
- Impactful Work: Lead high-impact projects that shape the future of digital advertising, directly influencing user experiences and business outcomes.
- Collaborative Culture: Join a team of talented engineers, researchers, and product professionals who are passionate about creating innovative, scalable, and cutting-edge ML solutions.
- Career Growth: Opportunities to expand your skills, grow into leadership roles, and shape the direction of ML research and development in the advertising space.
- Work-Life Balance: Enjoy flexible work options and a supportive environment that prioritizes well-being while driving innovation.
- Competitive Compensation: We offer a competitive salary, performance-based bonuses, stock options, and a comprehensive benefits package to support your work and life.
