לוח משרות דרושים בוגרי יחידות טכנולוגיות/אקדמיה משרה מלאה

The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk at Meta. The principal will enable the risk organization to deliver significant lift over current long range objectives for friction and leakage through the generation of new Machine Learning opportunities for the organization and support of successful delivery of the risk management ML architecture. This person will partner closely with the FRM engineering leader (Director level) and be part of Metas risk management leadership circle.
Software Engineer, ML (Technical Leadership) Responsibilities
Address core business and technical machine learning opportunities: elevate the existing portfolio of machine learning solutions to be state-of-the-art for minimizing Metas financial losses (due to leakage, good revenues loss and friction). Following are a few examples of technical and business problems we aim to address. - Provide a solution for optimizing the risk machine learning model ensemble (covering the entire end-to-end advertiser funnel including detection, decisioning, enforcement and remediation) through optimization of the current model portfolio and individual models. - Minimize the impact of the prolonged financial fraud feedback loop. - Improve models measurement and performance. - Optimize data/label strategy. - Optimize balance between specific targeted model strategy and broad umbrella model strategy to optimize for short and long term benefits
Lead Research and Introduction of Advanced Technologies: - Collaborate with Financial Integrity's senior ML Engineers to lead the research and introduction of deep learning and Large Language Model (LLM) technologies. - Remain current on industry-wide advancements in ML and introduce relevant advancements in Financial Risk Management
Collaborate on Next-Generation ML Architecture: - Work closely with financial harms principals and risk management tech leads to deliver the next-generation ML architecture for Meta's risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and Meta practices within the FRM team. - Resolve or mitigate design dilemmas, balancing business and technical trade-offs. - Identify and initiate opportunities for collaboration and impact with other organizations at Meta
Identify and Initiate New Business Opportunities: - Collaborate with Meta FinTech, Central Integrity and Core Ads Growth partnerships to identify and initiate new business opportunities based on third-party capabilities. - Conduct proof of concept for different opportunities and initiate integrations to enhance business performance
Grow Other Senior ML Engineers - Actively invest in the growth of other senior ML engineers through goal-driven formal and informal mentorship. Provide regular feedback to other engineers regarding their technical work

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
Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
Define and manage Service Level Agreements for all data sets in allocated areas of ownership
Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
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
Mentor team members by giving/receiving actionable feedback

We are the teams who create all of Meta's products used by billions of people around the world. Want to build new features and improve existing products like Messenger, Video, Groups, News Feed, Search and more? Want to solve unique, large scale, highly complex technical problems? Meta is seeking experienced full-stack Software Engineers to join our product teams. You can help build products that help us connect the next billion people, create new features that have billions of interactions per day and be a part of a team thats working to help people connect with each other around the globe. Join us!
Software Engineer - Infrastructure Responsibilities
Design core, backend software components
Code using primarily C/C++, Java, PHP and Hack
Interface with other teams to incorporate their innovations and vice versa
Conduct design and code reviews
Analyze and improve efficiency, scalability, and stability of various system resources
Establish self as an owner of a particular component, feature or system with expert end-to-end understanding
Successfully completes projects at large scope while maintaining a consistent high level of productivity

As a Solution Engineer in the Microsoft Innovation Hub, you will merge business and technical requirements to craft comprehensive solutions, working seamlessly with various stakeholders. You will conduct discovery sessions to understand customer needs and provide strategic recommendations and best practices tailored to their specific needs. Implementing robust AI transformation solutions and optimizing the integration of various technologies and services will be key aspects of your role. Additionally, you will leverage consultancy skills to foster collaboration among technical resources and stakeholders, ensuring alignment and effective teamwork. This role is Microsoft onsite only.



Responsibilities
Delivering customer engagements: Prepare and deliver technical engagements including strategy sessions, envisioning workshops, architecture design sessions and rapid prototyping to demonstrate key capabilities, validate against identified risks and finalize technology choices.

AI Transformation Leadership: Be the trusted voice within the business and for customers on the latest AI platform and technology trends, guiding their transformation journeys. By prioritizing AI use cases through design thinking workshops, you will lead these journeys effectively. You will be a valued contributor to Microsofts strategy in your area, ensuring the Hub is proactively aligned with the right customers to drive real impact.

Strategic Vision and Planning: Own and execute a clear strategic vision for AI transformation initiatives on a set of targeted accounts, aligning with organizational goals and customer needs by collaborating and orchestrating cross-functional teams.

Solution Design and Architecture: Develop comprehensive solution architectures based on patterns and practices that are tied to customer requirements and ensure that solutions are scalable, secure and optimized for performance. By utilizing consultation skills, you will uncover and prioritize opportunities, ensuing solutions are addressing real customer needs.

Cross Platform Collaboration: Adopt a holistic approach to integrate capabilities across the entire cloud platform, identifying synergies and optimizing cross-platform integration. You will work with your peers and stakeholders to make the Innovation Hub the home of Cross Solution AI Transformation.

Technical Depth: Maintain and grow expertise in creating business value on top of the business applications including sales, services and marketing and Microsoft 365 platform to support AI transformation initiatives. Stay updated with the market trends and collaborate with the technical communities.

Technical Sales and Sales Leadership: Act as a strategic change agent within the business to shape Microsoft's programs and engineering offerings. Lead the creation of scalable, field-relevant assets through internal communities. Champion Hub engagement success by connecting technical capabilities to sales opportunities and serving as a trusted voice with sales leaders and account teams.