Pembelajaran Mesin

Our engineers utilize state of the art models and continually push the boundaries of what’s possible in Snapchat's content, monetization, infrastructure, features, and more!

AI Lenses

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Machine Learning Engineering at Snap

As a Machine Learning Engineer at Snap you’ll drive Snapchat’s dynamic experience through the full lifecycle of advanced state-of-the-art models - from data preprocessing, feature engineering, and model training, to deployment and ongoing optimizations. You’ll leverage cutting-edge techniques, ranking algorithms for ad relevance, recommendation engines for personalized content and NLP for enhanced interactions - all while processing petabytes of data for over 850 million users.

Through both classic and deep learning models, you’ll create precise, responsive experiences that empower users to express themselves, connect and discover the world in real-time.

“The real benefit that Snap has is the size of our scale, and the breadth of influence and impact that people will have. You can run fast, have broad influence and actually see your work hit production with the right experimentation tools and infrastructure to be productive.”

Pasukan dalam Pembelajaran Mesin

Our machine learning engineers solve real world ML problems.

Pengewangan

Sebagai Jurutera Pembelajaran Mesin dalam pasukan Pengewangan, anda akan membina dan mengoptimumkan keseluruhan ekosistem iklan. Anda akan mendorong perkaitan tinggi dan berimpak tinggi untuk bukan sahaja pengiklan dan pengguna tetapi untuk semua Snap. Daripada mereka bentuk sistem berprestasi tinggi untuk pembidaan masa nyata atau penyajian dan lelongan iklan, memperibadikan penaraf ringan dan berat, mencipta penyelesaian untuk penyasaran dan penyampaian iklan, anda akan terus memastikan penyepaduan iklan yang lancar merentas platform. Anda akan melatih model tentang berbilion-bilion contoh, menggunakan pembelajaran berbilang tugas, pemodelan jujukan dan pemodelan interaksi pengguna x iklan. Model kami meramalkan demografi pengguna untuk meningkatkan audiens khalayak dengan rangkaian saraf dan kandungan graf, untuk memahami cara kerja kami membentuk masa depan platform iklan Snapchat.

Perkara yang akan anda usahakan:

Pengiklanan dipacu AI
Produk dan pengalaman iklan diperibadikan baharu
Pemilik pemacu hasil utama Snap
Membangunkan produk iklan termaju

Kandungan

Sebagai Jurutera Pembelajaran Mesin dalam pasukan Kandungan, anda akan berusaha membangunkan ciri untuk model pengesyoran video bentuk pendek yang sangat ketara yang memperkasakan kreativiti dan sambungan di teras platform kami seperti Cerita dan Tumpuan. Anda akan menumpukan pada meningkatkan pengalaman pengguna, memacu inovasi merentas Tumpuan, kedudukan Lensa, menyokong pencipta kandungan dan menjadikan penciptaan kandungan menjadi mudah. Pasukan kami menangani pemahaman kandungan berbilang mod, menggunakan representasi perwakilan graf lanjutan dan kedudukan kandungan untuk memaparkan pengalaman terbaik untuk pengguna kami. Kami mengoptimumkan model pembelajaran mesin melalui semakan manusia dan memanfaatkan teknik pemperibadian terkini, meletakkan kami di barisan hadapan dalam inovasi kandungan video bentuk pendek.

Perkara yang akan anda usahakan:

Cadangan kandungan yang diperibadikan
AI Generatif untuk penciptaan kandungan
Bangunkan ciri untuk produk yang sangat kelihatan seperti Tumpuan, Cerita, Suapan Terokai & cadangan Rakan

Core Growth

As a Machine Learning Engineer on the Core Growth team you’ll drive the search and friending experience across 15+ products, supporting over 100 million daily active users. 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

Platform

As a Machine Learning Engineer on the Platform Engineering team you’ll build models that provide timely, accurate, high quality and actionable data for decision making that forms the backbone of Snap's external reporting, experimentation, and ML/Ranking. Snap’s AI platform (aka 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

Trust & Safety

We want Snapchat to be a safe and positive experience for everyone who uses our platform or products. For this reason, we created rules and policies that explain the rights and responsibilities of all members of our community.

What you’ll work on:

Build Privacy-preserving AI
Launch new safety features

Generative AI

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

Locations

Our RTO (Return to Office) policy is 4 times per week hiring in these office locations

ML @ Snap

Dengar daripada pasukan tentang Kehidupan di Snap dalam Pembelajaran Mesin

We're Hiring!

Our interview process covers engineering, foundational, and applied ML.

Coding

Expect to solve algorithmic problems that test your proficiency in data structures, algorithms, and problem-solving skills. Focus on your ability to write clean, efficient, and well-documented code.

ML Fundamentals

You’ll be assessed on ML theory and core machine learning models, concepts, techniques and applications. Be prepared to discuss supervised and unsupervised learning, recommendation systems, ranking, model evaluation metrics, and optimization techniques.

ML Applied Design

Evaluates your ability to design and apply machine learning solutions to real-world problems. You may be asked to walk through the end-to-end process of selecting models, feature engineering, and evaluating performance. At times this can test your ability to problem solve in an ambiguous environment.

ML System Design

The focus will be on designing scalable and robust ML systems that can handle large-scale data and production environments. Expect to discuss the infrastructure and trade offs in architecture, model deployment strategies and system monitoring.

Our Interview Process