modeling, recommendation systems, information retrieval, and efficiency Build scalable research prototypes and evaluate them in large-scale machine learning scenarios

learning experience; or Master’s degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field Hands-on

Knowledge, Skills, & Abilities: Strong technical knowledge of statistics, machine learning, vision and state-of-the-art deep learning literature

Knowledge, Skills, & Abilities: Strong technical knowledge of statistics, machine learning, vision and state-of-the-art deep learning literature

machine learning engineering experience: taking models from idea to production, including training, evaluation, debugging, and iteration on large-scale data. Familiarity with

research or data-centric projects involving large-scale datasets. Strong technical knowledge of statistics, machine learning, vision and state-of-the-art deep learning

you’ll do:In this role, you will be working on client-side solutions that tie together graphics, computer vision, machine learning, and developer tools. Working in London, you’ll be collaborating

Infrastructure to join Snap Inc! What you’ll do: Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and

Leverage Artificial Intelligence (AI) and Machine Learning (ML) techniques to optimize system performance, automate complex troubleshooting, and enhance testing accuracy and efficiency

the Spectacles team and work on integrating Artificial Intelligence and Machine Learning models into the core operating systems and firmware. What you’ll do

Infrastructure and large-scale system design Security Networking and data storage Machine learning and

ranging from low-level embedded implementations to HLOS audio system architectures to audio signal processing and machine learning technology IP Participate in design reviews

). Experience integrating machine learning-based systems for content classification or ranking. Passion for building rich, innovative user

(e.g., machine learning, optimization) to solve real-world problems. Proven track record of delivering large scale projects in attribution and measurement

systems Infrastructure and large-scale system design Information Retrieval/Search Systems Machine learning for

Expertise: Deep expertise in large scale content, search, or content discovery systems, with a proven ability to integrate machine learning pipelines for automated content classification, ranking, and

with our cross-functional engineering and research teams in software engineering, computer vision, machine learning and graphics to write software for SnapOS, the operating system for Spectacles

Build privacy-preserving systems such as end-to-end encryption, private machine learning, data retention and deletion management solution Knowledge

Cloud computing and storage systems Infrastructure and large-scale system design Machine learning and natural language processing

feature stores, while driving innovations that enhance the efficiency and impact of Snapchat’s ranking and recommendation systems Design and optimize infrastructure systems for machine

black belt certification. Familiarity with machine learning and deep learning applications in

understand, debug and improve existing code as well as develop new algorithms using advanced computer vision and machine learning techniques.

and machine learning techniques. Ability to collaborate with other engineers and across different teams

understand, debug and improve existing code as well as develop new algorithms using advanced computer vision and machine learning techniques.

computer vision and machine learning techniques. Ability to collaborate with other engineers and across different teams

engineering, machine learning, data analytics, and program execution. TPMs at Snap are single-threaded owners of large-scale, high-stakes, and often ambiguous programs. They combine engineering depth with

software engineering, machine learning, data analytics, and program execution. TPMs at Snap are single-threaded owners of large-scale, high-stakes, and often ambiguous programs. They combine engineering

opportunities within Snap's long term roadmap for data-scientific contributions Conduct machine learning or statistical analyses, and build pragmatic, scalable, and statistically rigorous

technology company Experience using machine learning and statistical analysis for building data-driven product solutions or performing methodological research.

with AI, automation, and machine learning tools to enhance insight generation and delivery. Deep understanding of

, Stata, etc. Working knowledge of predictive modeling, machine learning, and experimentation/ causal inference methods Expertise in the data

, etc.) Understanding of computer LOGIC and Syntax Familiarity with machine learning and/or computer vision

experience in lieu of a degree 3+ years of experience working with technical xfn groups and technology, such as machine learning or related fields, to investigate and resolve

with machine learning, including LLMs Experience working with product and engineering teams to develop tools and solutions that improve trust across a platform or product

Familiarity with machine learning, including LLMs Ability to problem solve, both independently and with

ML models and commercializing them as products. Translate advertiser and business needs into ML requirements and guide a team of world class Machine Learning Engineers