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Required Design Verification Engineer, Networking, 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.
As a Design Verification Engineer, you will be a part of the Research and Development team to verify digital designs, develop constrained-random test environments and drive system testing to closure. You will collaborate with design and verification teams, manage the verification life-cycle and uncover bugs through corner-case testing.
Responsibilities
Plan and execute the verification of digital design blocks by understanding specifications and working with design engineers to define key verification scenarios.
Develop and refine random verification environments using SystemVerilog/Universal Verification Methodology (UVM) or Specman to ensure effective test coverage.
Define and implement various coverage measures to capture stimulus and corner-case scenarios.
Collaborate with design engineers to debug tests and ensure functional correctness of design blocks.
Drive coverage analysis to identify verification gaps and demonstrate progress towards tape-out.

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.

we are looking for a Research Scientist - Sovereign AI Research.
We are hiring across the following specializations. We expect depth in at least one area and the intellectual range to collaborate across them.
Computer Vision: object detection, segmentation, multimodal grounding, vision-language models, contrastive and self-supervised representation learning, low-resource and few-shot visual recognition.
NLP / Speech: LLMs, NERs, relation extraction, span-based and generative IE, semantic textual similarity, multilingual and cross-lingual transfer.
Reinforcement Learning: MDPs, POMDPs, model-based and model-free RL, Online Offline methods, reward modeling, sim-to-real transfer, compute-aware planning.
Graph Learning: GNNs, graph clustering, community structure, generative methods, knowledge graph embeddings, dense and sparse semantic retrieval.
Optimization: convex and nonconvex optimization, constrained and Lagrangian methods, combinatorial and integer programming, knowledge distillation (response, feature, and relation-based), test-time optimization, Bayesian optimization, resource-aware inference.
Representation Learning: contrastive learning, self-supervised and unsupervised pre-training, disentangled representations, metric learning and embedding spaces, cross-modal and multimodal alignment, meta learning (hypernetworks), transfer learning and domain adaptation, probing and interpretability of learned representations, world models.
Neurosymbolic AI: neuro-symbolic integration, differentiable theorem proving, inductive logic programming (ILP), probabilistic soft logic (PSL), causal inference and structural causal models (SCMs), programmatic and compositional reasoning
Responsibilities:
Define and execute a research within your track, experiments, quality gates, and upper bounds in rigorous manner.
Collaborate across tracks on system integration and cross-disciplinary research.
Collaborate work with engineering teams until production.
Mentor junior researchers and contribute to a culture of technical excellence

we are looking for a Applied AI Researcher.
The Dream-Maker Responsibilities
Open Research Tracks
Familiarity with at least one is expected:
Computer Vision: object detection, segmentation, multimodal grounding, vision-language models, contrastive and self-supervised representation learning, low-resource and few-shot visual recognition.
NLP / Speech: LLMs, NERs, relation extraction, span-based and generative IE, semantic textual similarity, multilingual and cross-lingual transfer.
Reinforcement Learning: MDPs, POMDPs, model-based and model-free RL, Online Offline methods, reward modeling, sim-to-real transfer, compute-aware planning.
Graph Learning: GNNs, graph clustering, community structure, generative methods, knowledge graph embeddings, dense and sparse semantic retrieval.
Optimization: convex and nonconvex optimization, constrained and Lagrangian methods, combinatorial and integer programming, knowledge distillation (response, feature, and relation-based), test-time optimization, Bayesian optimization, resource-aware inference.
Representation Learning: contrastive learning, self-supervised and unsupervised pre-training, disentangled representations, metric learning and embedding spaces, cross-modal and multimodal alignment, meta learning (hypernetworks), transfer learning and domain adaptation, probing and interpretability of learned representations, world models.
Neurosymbolic AI: neuro-symbolic integration, differentiable theorem proving, inductive logic programming (ILP), probabilistic soft logic (PSL), causal inference and structural causal models (SCMs), programmatic and compositional reasoning
Responsibilities:
Train and evaluate models across research tracks, iterating fast while documenting rigorously.
Build and maintain benchmarking pipelines and evaluation suites.
Curate, structure, and preprocess datasets; contribute to synthetic data generation workflows.
Run ablations and controlled experiments to support research hypotheses.
Reproduce and stress-test results from recent literature relevant to the group's work.
Collaborate across tracks and with engineering teams through to production handoff.

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.

The ATE Engineer is responsible for development of ATE test station development, including system architecture, test strategy, and transition from R&D to production. We are seeking a highly experienced professional with a strong background in RF, digital, and system-level testing, and with the ability to guide technical decisions, solve complex integration challenges, and support advanced test equipment for production environments.

What will you do:

Design and develop Automated Test Equipment (ATE) for RF, digital, and mixed-signal products at board and system levels.

Lead the technical definition and implementation of test strategies in collaboration with R&D, product engineering, and manufacturing teams.

Own the technical analysis of system schematics, block diagrams, and interface requirements to define robust and reliable ATE solutions.

Support production lines by troubleshooting test failures and optimizing test processes for yield and throughput improvements.

Provide technical guidance for integration with software and firmware control and automation systems.

Evaluate and select test instruments, fixtures, and measurement techniques based on product specifications.

Maintain documentation for test systems, including design files, calibration procedures, and troubleshooting guides.

Mentor engineers and technicians on ATE methodologies, operation, and maintenance.

we are looking for a Algorithm and Applied AI Scientist (DSP).
As an Algorithm and Applied AI Scientist (DSP), you will serve as the technical lead for an innovative project focused on advanced signal processing and data analytics applications. You will work with unique datasets from various signal-generating sources, researching and developing novel models, and analysing, maturing, and extracting features that have a significant impact on industrial manufacturers globally. In this role, you will be instrumental in defining project objectives, identifying customer value, and pushing the team toward successful outcomes. Joining AI team offers ongoing professional growth in leadership, algorithm development, research, innovations, and technical data analysis.
A Day In Your Life:
Be the technical lead of an innovative project.
Develop a comprehensive understanding of industrial data by exploring its physical properties and the relationships among different data streams.
Oversee the full algorithm development cycle, spanning from initial problem definition to the deployment of production-ready feature-based AI models, SDLC starting from feature discovery that is being tracked by sensor behavior patterns.
Architect and build diverse predictive and anomaly classification models using sensor time-series and textual information.
You will gain a deep proficiency in the industrial world and the connection between datasets to generate actionable insights.
Utilize classic and cutting-edge technologies, such as Generative AI, transformers, TSFM, TGNN, deep learning, and traditional statistical methods, time-series, and textual data to generate actionable insights.
Partner with the product team and external customers to create data-driven solutions that address real-world business needs.

​If you are looking to make an impact, come and join a team developing the next generation of space communication technology.

Our mission is to revolutionize the way satellites, space robots and spacecrafts communicate through deep space, in earth orbit and with ground stations. Our technology is based on space proven state-of-the-art proprietary architecture that enables a different approach to the way space communication systems are designed.

We are looking for experienced FPGA Engineers to lead innovation in the next generation space connectivity technology.



What you will be doing​

Design and manufacture systems including ICs by RS and SoC type FPGAs.

Design and implement high-speed digital signal processing algorithms.

Design for highly robust, distributed systems with emphasis on managing physical effects that originate from the harsh space environment.

Implement DSP algorithm on SoC type FPGAs.

Key contributor to Digital, Modem architecture and design.

Lead technical reviews with key stakeholders.

Work closely within a multi-disciplinary team to lead high-impact technical decisions about system design, implementation, and verification.

We are expanding our System Validation Group and invite you to explore Space with us!

Outstanding opportunity to be part of a super-cutting-edge team working on systems above and beyond the globe in our company.


What you will be doing​:

Writing system validation Test plans , Design and develop Test programs to validated embedded system features and performance.

Conducting System Validation Test cycles to verify systems based on HW (analog and Digital), RF, SW, FW

Experience with Python or C programing, Git or other programming languages & source control.

Strong technical troubleshooting.

Develop tools and utilities for Lab & field testing, feature analysis.

High debug capabilities when work with the Software, systems, HW teams on complex issues.

Ability to move fast and decisiveness.

Building development environment.

Designing automate tests.

E2E ownership product from kickoff to production.

Required Design Engineer, Edge AI, 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, youll work to shape the future of an Edge-AI product, bringing high-performance intelligence to the edge. You will have an opportunity to drive distributed inference technology that powers real-time systems where latency and reliability are mission-critical.
Youll be part of a team that pushes boundaries, developing robust, autonomous solutions that define the next generation of intelligent infrastructure and hardware for the edge. You'll contribute to the innovation behind products that transform industries, leveraging your expertise in system-level integration and localized processing to deploy complex AI models across sophisticated hardware platforms, ensuring intelligence is embedded exactly where the action happens.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of our platforms, we make product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Responsibilities
Lead a complex ASIC subsystem.
Understand how it interacts with software and other ASIC subsystems to implement groundbreaking data center.
Define high-performance hardware/software interfaces. Write micro architecture and design specifications.
Define efficient micro-architecture and block partitioning/interfaces and flows.
Collaborate closely with software, verification, and physical design stakeholders to ensure the designs are complete, correct, and performant.

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.

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.

Required Physical Design Engineer, SoC Static Timing Analysis
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.
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our direct-to-consumer products. In this role, you will contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering exceptional performance, efficiency, and integration.
We're the driving force behind our groundbreaking innovations, empowering the development of our cutting-edge 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
Drive the sign-off timing convergence for high-performance designs.
Set up the timing constraints, define the overall static timing analysis (STA) methodology, set up the STA infrastructure and sign-off convergence flows, and work closely with block owners throughout the project for sign-off timing convergence.
Work with logic designers to drive architectural feasibility studies, develop timing, and explore RTL/design trade-offs for physical design closure.