דרושים » מדעים מדוייקים » DSP Researcher

We are a rapidly growing startup company, developing the next-generation smart-infrastructure solution based on novel fiber-sensing technology (smart roads, smart cities, perimeters, and grid monitoring, etc). The company offers an award-winning disruptive solution; a sensor free approach to smart infrastructure. The company is VC backed and in the revenues stage. Combining pioneering technology in optical fiber sensing with state-of-the-art Machine Learning, we help prevent environmental disasters, protect human lives, and keep critical energy and transportation backbones running smoothly.
We are looking for a talented, self-driven, and hands-on Electro Optics Systems Engineer to join Photonics R&D team. In this role, you will develop and advance next-generation distributed fiber-optic acoustic sensing (DAS) systems, combining electro-optic system design, performance modeling, simulations, experimental validation, and field data analysis. You will tackle complex physical and engineering challenges, contribute to next-generation product development, and collaborate closely with multidisciplinary teams to bring innovative sensing technologies from concept to real-world deployment. This role is ideal for someone who thrives in a fast-paced, hands-on R&D environment, enjoys working across disciplines, and wants to see their work translate into real-world impact.
What Youll Do:
* Lead experimental and theoretical R&D efforts for the development of Prismas next-generation distributed fiber-optic acoustic sensing systems.
* Design, evaluate, and optimize electro-optic interrogation systems for distributed acoustic sensing applications.
* Develop system -level models and simulations for optical signal generation, fiber propagation, coherent detection, system noise, SNR, and sensing performance.
* Build software tools and simulations in Python, C ++, or similar languages for system evaluation, signal processing, field data analysis, and performance modeling.
* Plan, execute, and analyze laboratory and field experiments to validate system performance and support product development.
* Gain unique end-to-end expertise across the full sensing system pipeline, spanning fiber optics, electro-optics, coherent detection, DSP algorithms, and advanced data analysis.
* Lead product development activities from ideation and proof of concept through design, qualification, validation, and deployment.
* Collaborate closely with multidisciplinary R&D teams, including physicists, software engineers, algorithm developers, and hardware engineers.
* Communicate effectively with both technical and non-technical stakeholders, translating complex system behavior into clear insights and actionable recommendations.

Required Post-Silicon Validation Engineer
About The Position
We build cutting-edge radar chipsets for next-generation automotive sensing systems. As a Post-Silicon Validation Engineer, you will play a critical role in bringing complex mixed-signal ICs from silicon to system readiness.
Responsibilities
Perform validation of advanced radar ICs from bring-up through full functional and performance testing
Translate system and chip-level requirements into comprehensive validation plans and test cases
Develop automated test environments using lab instrumentation and custom scripts
Execute silicon bring-up and validate key subsystems (clocking, power, CPU, interfaces, sensors)
Perform electrical and parametric validation, including high-speed, power, and interface testing
Run characterization across PVT conditions and analyze large datasets
Debug complex silicon issues and work closely with design, verification, and system teams
Support device readiness for system integration and productization.

Required SoC Quality and Reliability Engineer, Cloud
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.
Our data centers are the most advanced in the world. In this role, you will help build the state-of-the art SoCs that power these data centers by driving quality and reliability processes from the Integrated Circuit perspective. This is an opportunity to create silicon and follow it into the field (and back!) to drive improvements for the next-generations of chips.
In this role, you will understand Integrated circuit (IC) flows, wafer processing, testing, qualification, yield, reliability, and failure analysis. You will work with various cross-functional teams to develop quality and reliability specifications, develop and deploy design guidelines, and develop and execute and test plans. Within the larger organization you will collaborate with global hardware quality and reliability teams, silicon design, validation and engineering teams.The AI and Infrastructure team is redefining whats possible. We empower customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity.
Responsibilities
Drive the strategic definition and development of Design-for-Reliability (DfR) guidelines, collaborating with cross-functional subject matter experts to integrate reliability into early design stages.
Define and lead the development of qualification hardware and test methodologies, managing internal teams and external vendors to ensure robust silicon and package verification.
Execute comprehensive silicon and package qualification programs (including HTOL, ELFR, ESD/LU, b/HAST, etc.) and conduct in-depth failure analysis to resolve quality issues.
Extract and analyze large-scale data from qualification programs, high-volume manufacturing, and field returns to identify failure mechanisms and trends for yield and reliability optimization.
Develop and implement physics-based statistical Quality and Reliability models (e.g., ELF, TDDB, NBTI) to predict device failure mechanisms and lifetime behaviors.

We are looking for some exceptional talent to join our Innovation team as an Advanced Technology Researcher.

Your Day to Day
Ownership of complex experimental systems and meeting challenging targets under tight deadlines
Lead and contribute to multidisciplinary research projects across advanced technologies and emerging domains
Design, execute, and analyze experiments, simulations, and proof-of-concept studies
Translate theoretical physics concepts into scalable, real-world applications
Collaborate closely with engineering, product, and cross-functional teams to drive innovation
Stay at the forefront of scientific and technological advancements and identify opportunities for integration
Present research findings clearly to both technical and non-technical stakeholders

Required Staff Embedded Firmware Engineer, High Speed DSP
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.
As a Staff Embedded Firmware Engineer for High-Speed DSP, you will architect and define the low-level firmware and control loops powering the world's most advanced physical-layer communications silicon. Sitting at the critical intersection of digital signal processing (DSP), hardware-software co-design, and real-time systems, you will lead the development of adaptive algorithms, error correction (FEC), and link-telemetry frameworks. Your work will directly bridge the gap between high-performance hardware pipelines and our planetary-scale AI infrastructure, transforming complex communication systems theory into reliable, real-time silicon execution.
Responsibilities
Define the long-term firmware roadmap and hardware-software partitioning for physical-layer interfaces, determining the optimal balance between hardware-fixed logic and programmable firmwarm.
Architect advanced "in-situ" monitoring systems and firmware-driven diagnostics to track physical-layer link health, Bit Error Rate (BER) trends, and channel quality across millions of ports in real-time.
Design, model, and implement bare-metal or RTOS firmware to control high-speed transceivers, managing real-time adaptive loops, clock and data recovery (CDR), and physical-layer calibration.
Partner with TPU Systems, Networking Software, and High-Performance Computing (HPC) teams to ensure silicon firmware integrates seamlessly with global cluster management and collective communication frameworks.
Identify and de-risk hardware-software interface bottlenecks (e.g., register maps, driver latencies, and boot-up sequencing) that impact our AI infrastructure.

Required Silicon Test and DFT Engineer, Cloud
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.The AI and Infrastructure team is redefining whats possible. We empower customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity.
We're behind groundbreaking innovations, empowering the development of AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Cloud, Global Networking, Data Center operations, systems research, and much more.
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 Automated Test Equipment (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.
Manage product sustainment support, including analyzing volume data, improving test time and yield, assessing test escapees and return merchandise authorizations (RMAs), localizing failures, implementing containment measures, and partnering with design, manufacturing, and quality and reliability teams to identify root causes and implement corrective actions.
Build tools, flows and methodologies to continuously improve and automate the testing life-cycle.

We are seeking a Senior Applied Researcher/ Data Scientist to join core product organization, where you will build and deploy next-generation AI models powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). The role centers on building and scaling intelligent systems powered by LLMs, advanced ML techniques, and agent-based architectures.
You will join a team within Cyber R&D organization, leading the companys core product portfolio-while driving AI innovation and setting best practices across the domain. The group focuses on developing next-generation technologies, including training and optimizing LLMs and building advanced multi-agent workflows, while mentoring data scientists across R&D.
As a key technical leader, you will guide the evolution of our AI capabilities-converting cutting-edge ideas into impactful, production-ready systems and shaping our long-term direction.
We are looking for visionary applied researchers eager to take on ambitious challenges and push the boundaries of AI in cybersecurity.
The Responsibilities:
Design and build advanced AI models and systems that power core products and address real-world cybersecurity challenges.
Own initiatives end-to-end from identifying customer-driven problems and shaping solutions to experimentation, prototyping, and production deployment.
Drive forward new ideas and research directions, turning emerging concepts into practical, scalable solutions.
Influence the organizations roadmap and contribute to long-term technical strategy across AI and product landscape.

Were looking for a talented Applied Algorithms & Operational Researcher to join our innovative team. As a member of our team, you will be responsible for analyzing extensive data, developing new metrics for our customers' vast data sets, and creating tools to classify and analyze the data effectively.
Responsibilities:
Conduct comprehensive performance analysis of automotive radar systems, including data collection, processing, and interpretation. Evaluate system performance in various scenarios.
Develop and implement algorithms and tools to process and analyze radar data. Extract relevant performance metrics and provide meaningful insights into system behavior and limitations.
Collaborate with the development team to identify areas for improvement and optimization.
Conduct radar system performance tests and validation procedures. Create test plans, define test cases, and analyze results to ensure system performance meets specified requirements. Identify potential issues, troubleshoot problems, and propose solutions.
Create concise reports, technical documents, and presentations summarizing performance analysis results and recommendations. Effectively communicate findings to cross-functional teams, including engineers, managers, and other stakeholders. Contribute to product documentation and technical specifications.

Our Network Architecture, Modeling and Performance Insights group is seeking a skilled and driven hands-on Network Modeling Architect to conduct advanced network research and optimization while utilizing and enhancing our advanced simulation tools.

In this role, you will be a key contributor to defining the architecture and improving network performance for AI and High Performance Computing (HPC) workloads. You will be responsible for modeling advanced network topologies, configurations, logic and traffic patterns, and analyzing their effect on end-to-end performance. You will develop expertise in our simulation tools and write code daily to contribute directly to their development road map and prioritization, develop core features in the simulator, and expose the capabilities to additional users. You will take part in complex architecture decisions, define and verify the modeling assumptions, and put them to the test vs. real HW and SW performance. If you're passionate about tackling intricate challenges and contributing to comprehensive systems and working on innovative solutions, we want to hear from you.

 

What you'll be doing:

Analyze and model our AI and High Performance Computing offerings, deep dive into network behavior for training and inference and generate insights to directly impact the architecture of next-generation of AI systems. Conduct advanced network modeling, research and optimization using innovative simulation tools.

Write production-quality C++ and Python code daily. Hands-on modeling of advanced network topologies, configurations and traffic patterns representing real life AI workloads, and analyze their effect on the system's performance. Actively develop the simulator software solution while contributing modular and scalable code.

Actively support the HW and SW development life cycles, map existing and candidate features into the simulation domain to enable their analysis, impact assessment and optimization.

Take full independent ownership of the performance modeling roadmap for a defined set of features. Interface directly with internal clients, communicate the analysis conclusions effectively and iterate on them. Drive projects from concept to completion.

Improve the quality of the simulation as a software product, ensuring robustness and reliability.

we are looking for a AI Applied Scientist - Insights & Recommendations.
As AI Applied Scientist, youll be at the intersection of advanced technology and meaningful impact with clear business cases. You will have access to real-time (RT) big data from multiple Sensors & Data sources, and a chance to discover, explore research, and develop cutting-edge models that directly impact industrial manufacturers around the globe. As part of the Applied AI/ML Science team , you will have the opportunity to continuously grow and learn while building and deploying advanced models directly into our products, and stay at the forefront of the world's technologies, witnessing firsthand their impact on our customers.
A Day In Your Life:
Own the algorithm lifecycle from problem definition and data analysis to prototyping and delivering production-ready models.
Combine classic methods with inference techniques: statistics, Time series, Deep learning, anomaly detection, Recommendation Systems, Transformers, and Inference to extract data-driven insights.
Research, design, and build Agentic applications on top of sensor time-series data, textual data, images, ML applications, and other various data sources.
Engage with customers and collaborate with our product team to develop innovative solutions utilizing new types of data.
Leverage modern technologies: work with cloud-based big data platforms for storage, distributed processing, LLMs and agents (GPT, Claude, Gemini), defining & building Gurdrails, reasoning chain as function call, planning, ML-based vectorization and embeddings, and stream analysis.