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As a Fraud Data Scientist, you will be at the front lines of protecting our ecosystem from sophisticated financial fraud and abuse. You will join a high-impact team operating in a data-rich, high-frequency environment where seconds matter.

In this role, you will take ownership of the end-to-end machine learning lifecycle-from uncovering complex fraud patterns to deploying highly scalable, real-time models into production. You will collaborate closely with Engineering, Product, and Risk Operations to build robust defenses that balance strict security with a seamless user experience.

What You Will Be Doing
Model Development & Deployment: Design, train, and deploy advanced machine learning models (e.g., gradient boosting, anomaly detection, graph networks) to detect and mitigate fraud in real-time.

Production Ownership: Take full ownership of putting models into production systems, ensuring low-latency execution and high reliability.

Agentic Workflows: Research, build, and implement Agentic flows and LLM-driven orchestration to automate multi-step fraud decisioning, logic routing, and investigation paths.

Adversarial Analysis: Conduct deep-dive exploratory analysis on massive datasets to identify emerging fraud vectors, loops, and coordinated attacks.

Feature Engineering: Build and optimize real-time streaming and batch features to improve model signal and precision.

Experimentation & Monitoring: Design rigorous shadow-testing and A/B testing frameworks for new models. Set up continuous monitoring pipelines to catch data drift and performance degradation early.

As we scale and evolve our fully automated fraud prevention strategies, we are seeking a Senior Data Analyst to join our growing Fraud Analytics team.

We operate in a data-rich, fast-paced environment, processing billions of data points annually, and play a critical role in safeguarding large enterprises from fraud. In this role, you will work at the intersection of data analysis, fraud strategy, and automation, collaborating closely with engineering, data science, and commercial teams to develop scalable fraud detection solutions.

This is a high-impact role with significant ownership and cross-functional collaboration in a team with tremendous room for growth. If you are highly motivated, data-driven, and thrive in a fast-moving environment - you belong with us.


Key Responsibilities

Develop and refine fraud detection strategies by analyzing complex datasets and identifying fraud patterns.

Partner with cross-functional teams, including software engineers, data scientists, and commercial stakeholders, to develop scalable fraud solutions.

Conduct deep-dive risk analyses, leveraging multiple data sources to assess fraud threats and define innovative solutions.

Monitor and automate fraud detection processes to enhance efficiency and effectiveness.

Required SoC Test Engineer, Cloud
About the job
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
Responsibilities
Collaborate with Architecture, Design and Verification teams to develop new product bring-up, validation, characterization, and qualification strategies and manufacturing test solutions for new High Performance Computing (HPC) products in advanced process technologies.
Verify test solutions on pre-silicon models (simulation or emulation) and develop ATE test modules and binning flows.
Develop and validate test programs on Automated Test Equipment (ATE) platforms for new product integration (NPI) in preparation for high volume manufacturing (HVM), working with ATE vendors and internal cross-functional teams.
Product sustain support, including volume data analysis, test time and yield improvements, assess test escapees and Return Merchandise Authorization (RMAs), localize failures, implement containment measures and partner with design, manufacturing, quality and reliability teams to root cause and implement corrective actions.
Develop tools, flows and methodologies to continuously improve and automate the testing life cycle.

We are seeking a Founding US Account Executive to play a key role in building our enterprise motion from the ground up.



What youll do:

Own the full sales cycle for enterprise customers, build relationships with leading global brands, and help shape our go-to-market strategy as we scale in the US.

Were looking for a BDR to join our growing Sales team and open the door to some of the biggest brands in the world.
What youll do

Own outbound into a set of Fortune 500 and leading global accounts, from first research to first meeting
Build account plans: who matters, what they care about, and how we get in
Write and test your own messaging across email, LinkedIn, phone, and any channel that works
Research and identify potential customers and key decision-makers, and build the prospecting lists to reach them
Create meaningful conversations, qualify opportunities, and generate real pipeline for the Sales team
Partner with Account Executives to sharpen the strategy on priority accounts
Track everything in our CRM and use what you learn to improve your approach week over week
Go deep on the Social Video Intelligence space and become fluent in digs product and value proposition

Required Senior CPU Design Verification Engineer, Cloud
About the job
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
In this role, you will work as part of a Research and Development team. You will build verification components, constrained-random testing, and system testing, and drive verification closure. You will verify digital designs, collaborate closely with design and verification engineers on projects, and perform direct verification. You will build constrained-random verification environments that exercise designs through their corner-cases and expose all types of bugs. You will manage the full life-cycle of verification, which can range from verification planning and test execution to collecting and closing coverage.
Responsibilities:
Plan the verification of digital design blocks by fully understanding the design specification and interacting with design engineers to identify important verification scenarios.
Create and enhance constrained-random verification environments using SystemVerilog and UVM, or formally verify designs with SystemVerilog Assertions (SVA) and industry leading formal tools.
Identify and write all types of coverage measures for corner-cases.
Debug tests with design engineers to deliver functionally correct design blocks.
Close coverage measures to identify verification holes and to show progress towards tape-out.

Required ML Hardware Achitect
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
In this role, you will help shape the future of Clouds next-generation AI infrastructure, architecting high-performance Machine Learning silicon designed to power hyperscale AI inference. You will have an opportunity to drive accelerator technology that powers Generative AI models, large language models (LLMs), and emerging agentic workloads where throughput, latency, memory bandwidth, and energy efficiency are mission-critical.
You will be part of a silicon architecture team pushing the boundaries of custom computing. Leveraging your deep expertise in hardware-software co-design, machine learning algorithms, and computer architecture, you will define and optimize custom compute engines and memory hierarchies that accelerate the world's most advanced AI models across Cloud datacenters.
Responsibilities
Lead the architectural definition, modeling, and specification of next-generation, high-performance ML compute IP and acceleration blocks for Cloud AI silicon.
Own the ML IP architecture specification throughout the entire product lifecycle: concept exploration, cycle-accurate modeling, implementation, silicon bring-up, and production.
Partner closely with leading AI research and algorithm teams (e.g., Google DeepMind, Gemini research teams) and software compiler teams (XLA, PyTorch) to explore architectural trade-offs and define hardware requirements for emerging model architectures.
Drive comprehensive architecture studies, evaluating compute dataflows, numerical formats, sparsity, and specialized acceleration mechanisms such as key-value (KV) cache optimization.
Drive performance, latency, power efficiency, and silicon area projections across model topologies and workload configurations.

We are looking for a jack of all trades. Someone happy to wear many hats and switch between them all day, who picks things up fast, thinks like an analyst, and brings great energy to the team.



What you will do



Onboarding: Drive the technical and operational rollout for new customers. Customize data views and reporting formats to each client's unique preferences, to ensure key insights are immediately accessible, intuitive, and actionable for their team.
Data Analysis: Analyze customer and product data, track performance metrics, and surface patterns and insights for both clients and internal teams.
Technical Support: Resolve product-related issues via email and own escalated cases end to end.
Prompt Engineering: Design, test, and refine prompts that power our product and customer setups.
Process Optimization: Monitor workflows, recommend new procedures, and roll out improvements using AI and automations to reduce friction and make our day-to-day faster.