Machine Learning Engineering Interview Prep

As a Machine Learning Engineer on the Platform Engineering team, you’ll build models that deliver timely, high-quality and actionable data to support decision-making across Snap's external reporting, experimentation, and ML/Ranking systems. Snap’s AI platform, Bento, powers many large scale ranking, recommendation, and Gen AI use cases. Over the past year, our scale of operations increased by 4-10X. You’ll develop embeddings that are consumed by downstream modeling teams. This team is mission critical to scaling and diversifying Snaps ML model offerings.

What you’ll work on:

• Highly available, multi-cloud infrastructure

• Optimizing the entire developer experience

• Ship high-quality features fast

Our Trust & Safety ML team builds advanced machine learning systems to protect the Snapchat community at massive scale. Our engineers develop NLP, computer vision, multimodal, and LLM-powered models to detect harmful content, abuse, scams, spam, and malicious behavior across Snapchat. The team invests heavily in modern ML techniques, including fine-tuning in-house and open-source LLMs, reinforcement learning, and distillation. Engineers own the full ML lifecycle, building robust, real-time systems where model quality and reliability have a direct impact on the safety of hundreds of millions of Snapchatters.

What you’ll work on:

• Develop and optimize LLM, NLP, computer vision, and multimodal models

• Build ML systems for content understanding, policy classification, and abuse detection

• Fine-tune, evaluate, and deploy models for safety-critical use cases

• Build scalable, real-time ML systems that protect the Snapchat community

As a Machine Learning Engineer on the Monetization team, you’ll build and optimize the entire ad ecosystem. You’ll drive high-relevance and impact for not only advertisers and users, but also for all of Snap. From designing high-performance systems for real-time bidding or ad serving and auctions, personalizing light and heavy rankers, to creating solutions for ad targeting and delivery, you’ll continue to ensure seamless integration of ads across the platform. You’ll train models on billions of examples, using multi-task learning, sequence modeling, and user x ad interaction modeling. Our models use graph neural networks and content signals to predict user demographics and improve  audience targeting, helping shape the future of Snapchat’s ad platform.

What you’ll work on:

• AI-driven advertising

• New personalized ad products and experiences

• Owner of Snap’s main revenue driver

• Developing cutting edge ad products

Our Generative AI team is at the forefront of innovation, shaping the future of augmented reality (AR) through SnapAR, which includes Lens Studio, Lens Engine, and Lens Cloud. Our engineers build real-time advanced AI models and machine learning models for dynamic transformations, such as realistic filters, object recognition, and scene understanding, ensuring seamless AR interactions for products like ML Lenses and Dreams. Lens Studio 5.0 stands out as the leading developer platform for creating cutting-edge Lenses that blend generative AI with traditional computer vision techniques. Generative AI empowers creators to design engaging lenses effortlessly without requiring expertise in 3D modeling, animation or coding.

What you’ll work on:

• Develop and optimize Generative AI Models

• Build AI-driven tools like text-to-3D generation

• Deliver generative AI and computer vision powered features

As a Machine Learning Engineer on the Content team, you’ll work on developing features for highly visible short form video recommendation models that power the creativity and connection at the core of our platform like Stories and Spotlight. You’ll focus on enhancing user experience, driving innovation across Spotlight, Lens ranking, supporting content creators, and making content creation effortless. Our team tackles multi-modal content understanding, using advanced graph representation learning and content ranking to surface the best experiences for our users. We optimize machine learning models through human review and leverage state-of-the-art personalization techniques, placing us at the forefront of short form video content innovation.

What you’ll work on:

• Personalized content recommendations

• Generative AI for content creation

• Develop features for highly visible products like Spotlight, Stories, Discover Feed & Friend suggestions

As a Machine Learning Engineer on the Core Growth team, you’ll drive the search and friending experience across 15+ products. Our team powers search for friends and content using advanced technologies, including graph databases, Large Language Models (LLMs), Mixture of Experts (MoE), and sophisticated machine learning stacks. You’ll develop search algorithms that connect users through friend and communication graphs, use visual and text embeddings for content discovery and enhance search with pretype recommendations that predict users queries. In addition to optimizing search infrastructure, the team’s friending products help users make real, meaningful connections to responsibly grow the Snapchat community. This work strengthens user engagement and retention, enabling other Snapchat features like messaging and story maps to flourish at scale. 

What you’ll work on:

• Create AR experiences

• Large scale system (5B notifications daily)

• Snapchat’s graph with 1+billion of nodes and hundreds of billions of edges