Snap
Consumer · Social
Currently tracking 6 active AI roles, with 56 new openings in the last 4 weeks. Primary focus: Serve · Engineering. Salary range $157k–$235k (avg $196k).
Consumer · Social
Snap currently has 8 active AI-related job listings. The majority of these roles are focused on serving infrastructure, accounting for 38% of the openings, followed by application and post-training stages, each representing 25%. Engineering is the most frequent function for these positions. The company is hiring for these roles in the United States and Austria. Frequent technology tags include model_serving, inference_infra, and recommender_systems. Over the last 30 days, Snap posted 1 new AI role, an 83% decrease compared to the previous 30-day period.
Snap currently has 15 active AI-related roles in our index. The most common open titles are: Computer Architecture Intern, Machine Learning Engineer, Generative ML , Level 5, Machine Learning Engineer, Level 4, Machine Learning Engineer, Level 5, Machine Learning Engineering Intern. Most positions are in Engineering and Product.
Snap's active AI hiring is concentrated in: application (40%), agents (27%), serving infrastructure (20%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Snap is hiring AI talent in: United States (11 roles), United Kingdom (1 role), Australia (1 role).
Job postings at Snap most frequently mention: Ranking & Relevance, Machine Learning, Computer Architecture, TensorFlow, System Design.
In the past 30 days, Snap has posted 5 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Computer Vision Engineer Computer Vision Engineer for Snap's Spectacles team, focusing on developing and deploying novel ML/CV algorithms for next-generation AR glasses. | Post-train | 8 |
| Machine Learning Engineer, Generative ML , Level 5 Machine Learning Engineer focused on building generative AI technologies for consumer-facing experiences on mobile, web, and wearables. The role involves developing full-stack generative AI, from foundational models to inference, and creating tools and agentic systems for creative applications, with a focus on image, video, and audio generation, as well as augmented reality. | ShipServe | 8 |
| Principal Machine Learning Engineer, Content ML, Level 7 Principal Machine Learning Engineer to lead the vision and roadmap for Snap’s large-scale recommendation systems, focusing on content discovery and personalization across various Snap products. The role involves technically leading engineers, collaborating with cross-functional teams on next-gen systems, and advancing the ML tech stack for recommendations. Requires deep understanding of RecSys architectures, ML/deep learning, and experience leading recommendation/personalization roadmaps, with a focus on shipping performant and scalable models. | Ship | 8 |
| Staff Machine Learning Engineer, Search Ranking Staff Machine Learning Engineer to lead the development of next-generation Search ranking systems. This role involves designing, building, and improving ML models for relevance, quality, personalization, and utility of search results at scale. Responsibilities include developing ranking models using various techniques, balancing multiple objectives, partnering with cross-functional teams, analyzing user behavior, designing evaluation frameworks, and improving ML infrastructure. The role also requires technical leadership and staying current with AI advancements in search and related fields. | ShipAgent | 8 |
| Machine Learning Engineer, CV Machine Learning Engineer focused on Computer Vision for next-generation Spectacles, developing and deploying ML models for real-world AR applications. | Serve | 8 |
| Working Student - Machine Learning Working student thesis project focused on developing efficient on-device ML models for AR glasses, specifically exploring event-based sensing and processing combined with deep learning techniques to meet strict latency, energy, and bandwidth constraints on embedded hardware. The role involves designing, prototyping, and evaluating models, exploring efficiency techniques, and demonstrating proof-of-concepts on AR hardware. | ServePost-train | 8 |
| Machine Learning Engineering Intern Machine Learning Engineering Intern to join the Spectacles AR engineering team, focusing on scene understanding for AR experiences. The role involves prototyping, training, and evaluating ML models for computer vision and multimodal understanding, contributing to geometric scene understanding, 3D reconstruction, semantic scene understanding, visual localisation, and connecting scene understanding to language for AR interactions. The intern will partner with mentors and cross-functional teams to integrate work into production-facing systems. | Post-trainAgent | 8 |
| Staff Software Engineer, Platform Engineering Staff Software Engineer to join the Platform Engineering team, focusing on building AI-powered testing tools and infrastructure. This includes agent harnesses, evaluation systems, Temporal-based workflows, and telemetry-driven debugging capabilities to improve developer productivity and software quality across Snapchat's mobile apps and backend services. | AgentEval Gate | 7 |
| Software Engineer, ML Infrastructure, Level 4 Software Engineer, ML Infrastructure at Snap, focusing on scaling ML infrastructure, optimizing training and inference systems, and improving ranking and recommendation systems. The role involves designing and optimizing infrastructure for ML workloads, building feature generation and serving pipelines, developing high-performance inference systems, and managing data for ML training and evaluation. | ServeData | 7 |
| Machine Learning Engineer, Level 4 Machine Learning Engineer at Snap focused on building and deploying ML models for core consumer products, owning the full ML lifecycle, and applying modern ML techniques to large-scale problems. The role involves partnering with cross-functional teams and utilizing AI tools responsibly. | ShipServe | 7 |
| Machine Learning Engineer, Level 5 Machine Learning Engineer at Snap Inc. responsible for building and deploying ML models for core products, owning the full ML lifecycle, and applying modern ML techniques to solve large-scale problems. The role involves partnering with cross-functional teams and utilizing AI tools for scalable service design and deployment, with a focus on code correctness, security, and production standards. Experience in ranking, recommendations, search, content understanding, or image generation is required. | Ship | 7 |
| Computer Architecture Intern Computer Architecture Intern to implement, map, and simulate neural rendering algorithms on event-based Neural Processing Units (NPUs), perform benchmarking, and identify hardware/compiler improvements for efficiency. | Serve | 7 |
| Software Engineer C++, Level 4 Software Engineer C++ focused on AI tooling for AR application development, building agentic workflows for Lens Studio, and implementing software for compute-constrained AR glasses. | Agent | 7 |
| Spectacles Student Worker- Computer Vision Engineering Computer Vision Engineering student worker role focused on researching and developing advanced computer vision algorithms and implementing them onto Spectacles. The role involves optimizing performance, writing clean code, and potentially publishing research or contributing to patents. | Post-train | 7 |