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We are looking for AI Engineer to join the Data Science team.

As an AI Engineer in the Data Science team, you will be working closely with applied researchers on model optimizations, GPU and hardware, language-model optimizations in the Video and Language domains and more. Your code will reach Azure resources and extensions, and you will use various technology stacks with the latest tools and methodologies. You will be expected to ;break down problems, learn and develop, have an open mind, and have ownership all the way to production. Working in a multi-disciplinary team will require excellent communication skills and at the heart of it all, alignment with Microsoft values and endless curiousness.

We are looking for a Senior Cloud Solution Architect (CSA), specializing in Data Security who is passionate about driving our customers security & AI transformation on the Microsoft Platform. Microsoft Data Security Cloud Solution Architects are trusted advisors for customers attempting to secure their entire data estates against internal and external data risk. Microsoft Purviews integrated Data Security services support customers holistically secure data:

Protect sensitive information using data classification, sensitivity labelling and encryption capabilities.
Manage insider risks by using machine learning to detect potentially malicious usage, extending into adaptive protection to dynamically enforce data security controls.
Prevent Data Loss using built in exfiltration policies for Microsoft 365 apps, services and endpoints.

As a Data Engineer at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs, Threads). Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide.

In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across Meta to optimize growth, strategy, and user experience for our 3 billion plus users, as well as our internal employee community.

You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining Meta, you will become part of a world-class data engineering community dedicated to skill development and career growth in data engineering and beyond.

Data Engineering: You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, design logging solutions, and create scalable data models. Ensuring data security and quality, and with a focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems.

Product leadership: You will use data to shape product development, identify new opportunities, and tackle upcoming challenges. You'll ensure our products add value for users and businesses, by prioritizing projects, and driving innovative solutions to respond to challenges or opportunities.

Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Engineer, Product Analytics Responsibilities
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Define and manage Service Level Agreements for all data sets in allocated areas of ownership
Solve challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
Improve logging
Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
Influence product and cross-functional teams to identify data opportunities to drive impact