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we are looking for a Failure Analysis Engineer.
Job Description:
Lead fault isolation and root cause analysis of memory and logic failures, including electrical, test, and yield failures, from initial failure signature through physical confirmation
Analyze failures at device, memory-cell, array, and circuit level, differentiating between design, test, device, process, and physical failure mechanisms
Correlate electrical characterization, memory-test and yield results, schematics, layout, and physical FA findings to identify and validate root cause
Develop and execute effective fault-isolation strategies, localizing failures down to the relevant cell, circuit, interconnect, or physical structure
Work closely with Design, Device, Test/Product, Process, Reliability, and Physical FA labs to solve complex failures and drive corrective actions
Improve FA methodologies, prepare and present engineering FA report on complex failure investigations

Be part of the team that is responsible for developing and optimizing the state-of-the-art analog circuits that power our embedded ReRAM and mixed-signal products.
In this role, you will take the lead on designing high-performance analog circuits, driving innovation in mixed-signal systems from concept through production. Youll partner closely with digital design, system architecture, and process engineering teams, playing a key role in bringing our next generation of memory products to market:
Design and develop complex analog circuits, including amplifiers, complex memory arrays, and LDOs, ensuring reliability and performance
Collaborate with cross-functional teams to define system specifications and architecture, translating requirements into actionable designs
Conduct thorough simulations and analyses to validate designs, using tools such as Cadence Virtuoso and Siemens Solido while identifying and mitigating risks early in the design process
Oversee the transition of designs from prototype to production, ensuring compliance with quality and industry standards
Apply deep expertise in analog circuit design - including amplifiers, voltage references, comparators, and ADCs/DACs - to push the boundaries of performance

we are looking for a Sr. Memory Architect.
A senior memory architect to lead the development of Novel NVM modules in advanced nodes using state-of-the-art EDA tools
Proven ability to lead a memory design from the architecture exploration phase, through block level design & layout up to full module assembly, verification & characterization
Interaction with product marketing & customers to analyze & propose memory architectures meeting the needs of the customer

At ThetaRay, our purpose is to make the world a safer place by protecting the integrity of the global financial system. We do this by putting AI at the core of both our technology and our way of working. Our AI-driven solutions help banks and fintech companies worldwide detect and stop serious financial crime, from human trafficking and terrorist financing to sophisticated money laundering, while advanced technology, automation, and AI-driven tools help our teams collaborate smarter, move faster, and continuously improve how we build, deliver, and innovate.
About the role: We are looking for an Algorithm Researcher to turn expertise, initiative, and bold thinking into real impact on the next generation of AI-driven financial crime detection.
If you combine strong mathematical and research capabilities with advanced AI expertise, and if you are motivated by turning complex theoretical concepts into scalable, production-ready algorithms that solve real-world financial crime challenges, ThetaRay could be your next challenge.

?Responsibilities:
* Designing and developing advanced algorithms for complex financial crime detection challenges
* Translating mathematical models and research concepts into scalable production systems
* Building and optimizing ML and LLM-based solutions for real-world deployment
* Working with transformers, attention mechanisms, sequence modeling, and representation learning
* Developing solutions using RAG, embedding models, vector databases, and generative AI evaluation frameworks
* Designing AI agents, tool-using LLM architectures, and autonomous decision-making pipelines
* Improving model accuracy, robustness, explainability, and inference efficiency
* Collaborating with engineers, data scientists, and domain experts to bring research into production