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The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk . 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 PM here, you own one of those systems end to end: you set the strategy, work daily with a team of engineers and data scientists in Tel Aviv, and drive decisions that show up in company-level growth numbers. The problems are genuinely hard and mostly unsolved - how do you prove the value of a channel you can't fully instrument, how do you respond to an ecosystem highly disrupted by AI, how do you make someone want an app before you ask them to sign up.
Product Manager, Central Products Responsibilities
Is the primary driver for identifying significant near and long-term opportunities in a large Product area, and driving product mission, strategies, and roadmaps in the context of broader organizational strategies and goals
Generate buy-in and drive consensus across organizations. Bring clarity and structure to ambiguous opportunities. Consistently demonstrate initiative and execute with limited oversight
Critically evaluate when AI is (and isn't) the optimal solution at portfolio level, setting the standard for rigorous tradeoff analysis
Translate AI capabilities into compelling, differentiated product visions that define market categories
Champion AI-native strategies including comprehensive evals and data strategies that enable org-wide continuous improvement
Drive product development with teams of engineers and designers, while maintaining team health
Work closely with cross-functional teams to drive product mission, define product requirements, coordinate resources from other groups (design, legal, etc.), develop roadmaps, and guide the team through key milestones
Reimagine workflows, responsibly using AI tools to transform team velocity and capability at organizational scale
Foster a culture of rapid experimentation and learning that becomes a competitive advantage
Scale AI best practices (including responsible AI use), workflows, and artifacts across the organization so capability compounds exponentially
Plan, initiate, and manage information technology projects for web-based products, applications, and platforms
Orchestrate complex execution across multiple organizations by combining AI automation with strategic human oversight at scale
Maximize efficiency in a constantly evolving environment where the process is fluid and creative solutions are the norm
Use AI-enabled tools to build products-setting the standard for PM technical capability
Interpret research and state-of-the-art learnings to design product strategy and apply rigorous logical reasoning at the frontier
Demonstrate expert understanding of system/architecture trade-offs and how they impact user experience and business outcomes; lead strategic technical decisions with engineering leadership
Integrate data, usability studies, research, and market analysis into product strategies and requirements to enhance user satisfaction and improve engineer productivity
Express complex and technical concepts at the right altitude, choosing the right medium and level of detail for the audience (XFN partners, execs, engineering, etc.)
Understand Meta's strategic and competitive position and deliver products that are aligned with our mission and recognized best in the industry
Define and analyze metrics that inform the success of products. Identify and track key performance metrics. Drive decision-making through user insights, quantitative analysis, and AB testing
Design sophisticated experiments and interpret results (leveraging AI) to drive strategic product decisions
Define and run evaluations (evals) to interpret model outputs at scale-establishing evaluation as a strategic capability for AI-powered experiences

we are looking for a hands-on Data Platform Engineer to operate and evolve our enterprise Kafka ecosystem, which serves as the companys central data streaming platform. The role is critical to our data infrastructure and supports a major ongoing migration to the cloud, while covering production operations, troubleshooting, automation, maintenance, and reliability across high-volume, low-latency, 24/7 on-premises and cloud environments.
Responsibilities:
Operate and monitor Kafka environments across Confluent Cloud, Confluent Platform, and Kubernetes/CFK deployments, including availability, consumer lag, replication, throughput, latency, storage, and capacity.
Troubleshoot production incidents, participate in on-call, perform root-cause analysis, and improve resilience, failover, and disaster-recovery readiness.
Manage topics, partitions, retention, ACLs, consumer groups, Kafka Connect connectors, and Schema Registry.
Deploy, configure, upgrade, patch, and scale platform components and connectors while maintaining secure access and configuration consistency.
Automate platform operations and provisioning using scripting, infrastructure-as-code, and CI/CD.
Work with DevOps, SRE, Infrastructure, Security, Architecture, Data, and application teams to onboard workloads and continuously improve platform reliability and governance.

We are looking for a Senior Enterprise Architect - Core Payments Processing to join our Architecture team. Reporting to the VP of Architecture, you will play a key role in shaping and delivering the architecture of next-generation payment processing platforms.
In this role, you will be responsible for designing and guiding the implementation of highly scalable, resilient, and secure transaction-processing systems supporting global payment operations. You will work closely with Product, Engineering, DevOps, Security, and Data teams to translate complex business requirements into robust technical solutions.
This role requires deep experience in real-time distributed systems, fintech/payment platforms, and modernization of large-scale systems, as well as the ability to influence cross-functional teams and ensure architectural integrity throughout delivery.
You will help evolve platform by balancing long-term architecture strategy with pragmatic delivery, enabling the company to scale its global payment capabilities while maintaining reliability, compliance, and operational excellence.

We are looking for a motivated Mid - Level Salesforce Developer (1-3 years of experience) to join Business Automation team. This role is an excellent opportunity for someone looking to grow their Salesforce development career while working on enterprise-scale projects, integrations, and business process automation initiatives across multiple departments.
Responsibilities:
Develop and maintain Salesforce solutions using Apex, Lightning Web Components (LWC), and Flow.
Configure and customize Salesforce objects, fields, page layouts, validation rules, and automation.
Support integrations between Salesforce and internal/external systems.
Assist in troubleshooting production issues, bugs, and user-reported problems.
Collaborate with Salesforce Administrators, Business Analysts, and business stakeholders to deliver efficient solutions.
Participate in testing, deployment, and release management activities.
Follow Salesforce development best practices, coding standards, and security guidelines.
Document technical designs, configurations, and development work.

we are looking for a AI Product Owner.
As an AI Product Owner & AI Process and Agentic Designer, you will own the process of transforming complex workflows into scalable AI solutions, bridging the gap between business stakeholders and AI Engineers. You will lead business process analysis, identify agentic process opportunities, validate business value, and define solution designs that enable successful AI implementation across the organization.
Responsibilities:
Business Process Analysis & Discovery
Partner with business stakeholders to map, document, and analyze existing workflows, identifying inefficiencies, bottlenecks, and manual processes ripe for automation.
Conduct discovery sessions and workshops to deeply understand business needs, pain points, and success criteria across departments.
Agentic Opportunity Identification
Evaluate workflows to pinpoint where agentic and AI-driven approaches can deliver the most value, distinguishing tasks suited to automation, augmentation, or full agentic orchestration.
Maintain a prioritized pipeline of AI/agentic opportunities, assessing each for feasibility, complexity, and impact.
Business Value Validation
Define and quantify the expected business value of proposed solutions (e.g., cost savings, time reduction, quality improvement, revenue impact) and build the business case for investment.
Establish success metrics and KPIs, and track realized value post-implementation to ensure outcomes match projections.
Solution Design & Definition
Translate business requirements into clear solution designs, including agentic process flows, decision logic, data inputs/outputs, integration points, and human-in-the-loop checkpoints.
Define guardrails, escalation paths, and fallback behaviors to ensure solutions operate safely and reliably.
Stakeholder & Engineering Bridging
Serve as the primary liaison between business stakeholders and AI engineers, translating business intent into technical requirements and engineering constraints back into business terms.
Own the product backlog, prioritize features, and clearly communicate scope, trade-offs, and timelines to all parties.
Implementation Enablement & Iteration
Guide solutions through the full lifecycle from concept to deployment, supporting testing, validation, and change management.
Gather feedback, monitor performance, and drive continuous refinement of deployed AI and agentic solutions.
Scalability & Standardization
Identify reusable patterns, components, and best practices to scale successful solutions across the organization.
Contribute to governance frameworks, documentation standards, and design principles for AI/agentic product development.

We are looking for a Senior Full Stack Developer to join our fast-growing team. You will report to the Full Stack Team Leader and play a key role in contributing to our teams ongoing success and growth.
Responsibilities :
Design, develop, and maintain high-performance web applications using React and TypeScript, incorporating advanced AI features into the user experience.
Building and optimizing robust backend APIs to support payment workflows, including multi-agent state management and LLM lifecycle governance.
Collaborate cross-functionally with product managers, architects, DevOps, and UX/UI designers to translate business requirements into comprehensive, scalable solutions.
Drive development efficiency by leveraging AI-assisted tools to improve code velocity, consistency, and overall system reliability.