At Synopsys, we drive the innovations that shape the way we live and connect. Our technology is central to the Era of Pervasive Intelligence, from self-driving cars to learning machines. We lead in chip design, verification, and IP integration, empowering the creation of high-performance silicon chips and software content.
\nAs a Memory Compiler Architect, you will be responsible for designing, developing, and evaluating physical IP,Memory compilers (SRAM/RF/ROM/TCAM etc.). You will apply expertise in circuit design, memory architecture optimization for best-in-class PPA and industry-standard verification tools to optimize workflows and enhance design efficiency.
\nCollaborate with cross-functional teams to align project deliverables with business objectives. Contribute to the technical direction and problem-solving efforts within the engineering group. Share knowledge and support the professional growth of team members through technical mentorship.
\nAdvance our product portfolio with innovative solutions addressing market demands. Improve the efficiency and effectiveness of engineering development workflows. Solve complex engineering challenges, contributing to successful project outcomes. Support the growth and technical development of colleagues through guidance and collaboration.
\nKey responsibilities include:
\nRequirements include:
\nThe ideal candidate will be an effective communicator who engages and influences stakeholders. A strategic thinker with a passion for innovation. A collaborative professional who thrives in a dynamic, fast-paced environment. A mentor willing to share expertise and support the technical growth of peers. A problem-solver with keen attention to detail.
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_ac561bbf-75b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Synopsys","sameAs":"https://careers.synopsys.com","logo":"https://logos.yubhub.co/careers.synopsys.com.png"},"x-apply-url":"https://careers.synopsys.com/job/sunnyvale/memory-compiler-architect-15954/44408/93816738528","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$226,000-$338,000","x-skills-required":["Embedded memory design","Functional verification","Python","Hspice/XA","Industry-standard verification tools"],"x-skills-preferred":["Circuit design","Memory architecture optimization","Best-in-class PPA","Technical mentorship"],"datePosted":"2026-04-24T14:11:34.637Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Sunnyvale"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Embedded memory design, Functional verification, Python, Hspice/XA, Industry-standard verification tools, Circuit design, Memory architecture optimization, Best-in-class PPA, Technical mentorship","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":226000,"maxValue":338000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_69d1c48a-3f1"},"title":"Senior Software Engineer–Backend–Microsoft Copilot","description":"As Microsoft continues to push the boundaries of AI, we are on the lookout for passionate individuals to work with us on the most interesting and challenging AI questions of our time. Our vision is bold and broad , to build systems that have true artificial intelligence across agents, applications, services, and infrastructure. It’s also inclusive: we aim to make AI accessible to all , consumers, businesses, developers , so that everyone can realize its benefits.
\nOur Platform team is responsible for building and scaling the backend platform at the core of Microsoft consumer products, the integrations with our AI models and the tools that our engineers use. We collaborate closely with cross-functional engineering, product management, and AI research, empowering all Microsoft Copilot teams to more effectively bring cutting-edge AI research to production.
\nWe’re seeking experienced Platform Infrastructure Engineers who are passionate about AI, are deeply proficient in scaling backend technologies, and possess a mastery of templating to architect solutions that stand the test of time.
\nResponsibilities:
\nQualifications:
\nPreferred Qualifications:
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_69d1c48a-3f1","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-software-engineer-backend-microsoft-copilot/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["C","C++","C#","Java","JavaScript","Python","Docker","Kubernetes","nginx","RDBMS","key-value stores"],"x-skills-preferred":["Master’s Degree in Computer Science or related technical field","6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python","Solid experience in designing and building scalable backend services, APIs, and distributed systems in cloud environments","Solid understanding of system design principles, including data modeling, caching strategies, and service-to-service communication (e.g., REST, gRPC)","Ability to troubleshoot and resolve complex backend issues across multiple services, with a focus on reliability, performance, and scalability","Proficiency in writing clean, maintainable, and testable code, with a solid emphasis on code quality, observability, and security best practices","Experience working with databases (SQL/NoSQL), and a deep understanding of data consistency, indexing, and query optimization","Demonstrated ability to collaborate effectively with cross-functional teams, including frontend engineers, product managers, and infrastructure teams","Solid communication skills, with the ability to explain backend architectures and technical trade-offs to both technical and non-technical stakeholders","Ability to operate in a fast-paced environment, handle ambiguity, and manage multiple priorities with a solid sense of ownership","Passion for backend technologies and distributed systems, with a continuous learning mindset toward new frameworks, architectures, and AI-driven backend capabilities","Proven track record of contributing to team growth through code reviews, technical mentorship, and knowledge sharing"],"datePosted":"2026-04-24T12:13:17.926Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Beijing"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"C, C++, C#, Java, JavaScript, Python, Docker, Kubernetes, nginx, RDBMS, key-value stores, Master’s Degree in Computer Science or related technical field, 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python, Solid experience in designing and building scalable backend services, APIs, and distributed systems in cloud environments, Solid understanding of system design principles, including data modeling, caching strategies, and service-to-service communication (e.g., REST, gRPC), Ability to troubleshoot and resolve complex backend issues across multiple services, with a focus on reliability, performance, and scalability, Proficiency in writing clean, maintainable, and testable code, with a solid emphasis on code quality, observability, and security best practices, Experience working with databases (SQL/NoSQL), and a deep understanding of data consistency, indexing, and query optimization, Demonstrated ability to collaborate effectively with cross-functional teams, including frontend engineers, product managers, and infrastructure teams, Solid communication skills, with the ability to explain backend architectures and technical trade-offs to both technical and non-technical stakeholders, Ability to operate in a fast-paced environment, handle ambiguity, and manage multiple priorities with a solid sense of ownership, Passion for backend technologies and distributed systems, with a continuous learning mindset toward new frameworks, architectures, and AI-driven backend capabilities, Proven track record of contributing to team growth through code reviews, technical mentorship, and knowledge sharing"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2c095439-13b"},"title":"Principal Software Engineer","description":"Microsoft Advertising is seeking a Principal Software Engineer to join our Ads Engineering Platform team and advance the core capabilities of our ad-serving infrastructure,the engine that powers advertising across Bing Search, MSN, Microsoft Start, and shopping experiences in the Edge browser.
\nOur serving stack operates at massive global scale, delivering millions of ad requests per second through a geo-distributed, low-latency system that combines large-scale GPU/CPU inference, real-time bidding, and intelligent ranking pipelines.
\nThis role focuses on advancing the performance, efficiency, and scalability of the next generation of model serving and inference platforms for Ads.
\nAs a senior technical leader, you’ll design and optimize high-performance serving systems and GPU inference frameworks that drive measurable latency improvements and cost efficiency across Microsoft’s ad ecosystem.
\nYou’ll work across the stack,from CUDA kernel tuning and NUMA-aware threading to large-scale distributed orchestration and model deployment for deep learning and LLM workloads.
\nThis is a rare opportunity to shape the architecture of one of the world’s most advanced, mission-critical online serving platforms, collaborating with world-class engineers to deliver innovation at Internet scale.
\nMicrosoft’s mission is to empower every person and every organization on the planet to achieve more.
\nAs employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals.
\nEach day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nStarting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week.
\nThis expectation is subject to local law and may vary by jurisdiction.
\nResponsibilities:
\nDesign and lead the development of large-scale, distributed online serving systems,including GPU-accelerated and CPU-based ranking/inference pipelines,to process millions of ad requests per second with ultra-low latency, high throughput, and solid reliability.
\nArchitect and optimize end-to-end inference infrastructure, including model serving, batching/streaming, caching, scheduling, and resource orchestration across heterogeneous hardware (GPU, CPU, and memory tiers).
\nProfile and optimize performance across the full stack,from CUDA kernels and GPU pipelines to CPU threads and OS-level scheduling,identifying bottlenecks, tuning latency tails, and improving cost efficiency through advanced profiling and instrumentation.
\nOwn live-site reliability as a DRI: design telemetry, alerting, and fault-tolerance mechanisms; drive rapid diagnosis and mitigation of performance regressions or outages in globally distributed systems.
\nCollaborate and mentor across teams,driving architecture reviews, enforcing engineering excellence, promoting system-level optimization practices, and mentoring others in deep debugging, profiling, and performance engineering.
\nQualifications:
\nRequired Qualifications:
\nBachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
\nPreferred Qualifications:
\nMaster’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
\nIndustry experience in advertising or search engine backend systems, such as large-scale ad ranking, real-time bidding (RTB), or relevance-serving infrastructure.
\nHands-on experience with real-time data streaming systems (Kafka, Flink, Spark Streaming), feature-store integration, and multi-region deployment for low-latency, globally distributed services.
\nFamiliarity with LLM inference optimization,model sharding, tensor/kv-cache parallelism, paged attention, continuous batching, quantization (AWQ/FP8), and hybrid CPU–GPU orchestration.
\nDemonstrated success operating large-scale systems with SLA-based capacity forecasting, autoscaling, and performance telemetry; proven leadership in cross-functional architecture initiatives and technical mentorship.
\nPassion for performance engineering, observability, and deep systems debugging, with a solid drive to push the limits of serving infrastructure for the next generation of ads and AI models.
\nDeep expertise in GPU inference frameworks such as NVIDIA Triton Inference Server, CUDA, and TensorRT, including hands-on experience implementing custom CUDA kernels, optimizing memory movement (H2D/D2H), overlapping compute and I/O, and maximizing GPU occupancy and kernel fusion for deep learning and LLM workloads.
\nSolid understanding of model-serving trade-offs,batching vs. streaming, latency vs. throughput, quantization (FP16/BF16/INT8), dynamic batching, continuous model rollout, and adaptive inference scheduling across CPU/GPU tiers.
\nProven ability to profile and optimize GPU and system workloads,including tensor/memory alignment, compute–memory balancing, embedding table management, parameter servers, hierarchical caching, and vectorized inference for transformer/LLM architectures.
\nExpertise in low-level system and OS internals, including multi-threading, process scheduling, NUMA-aware memory allocation, lock-free data structures, context switching, I/O stack tuning (NVMe, RDMA), kernel bypass (DPDK, io_uring), and CPU/GPU affinity optimization for large-scale serving pipelines.
\n#MicrosoftAI Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 – $304,200 per year.
\nCertain roles may be eligible for benefits and other compensation.
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_2c095439-13b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-software-engineer-41/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$139,900 - $274,800 per year","x-skills-required":["C","C++","C#","Java","JavaScript","Python","NVIDIA Triton Inference Server","CUDA","TensorRT","Kafka","Flink","Spark Streaming","GPU inference frameworks","LLM inference optimization","model sharding","tensor/kv-cache parallelism","paged attention","continuous batching","quantization","AWQ/FP8","hybrid CPU–GPU orchestration","SLA-based capacity forecasting","autoscaling","performance telemetry","cross-functional architecture initiatives","technical mentorship","performance engineering","observability","deep systems debugging","low-level system and OS internals","multi-threading","process scheduling","NUMA-aware memory allocation","lock-free data structures","context switching","I/O stack tuning","kernel bypass","CPU/GPU affinity optimization"],"x-skills-preferred":[],"datePosted":"2026-04-24T12:12:57.301Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"C, C++, C#, Java, JavaScript, Python, NVIDIA Triton Inference Server, CUDA, TensorRT, Kafka, Flink, Spark Streaming, GPU inference frameworks, LLM inference optimization, model sharding, tensor/kv-cache parallelism, paged attention, continuous batching, quantization, AWQ/FP8, hybrid CPU–GPU orchestration, SLA-based capacity forecasting, autoscaling, performance telemetry, cross-functional architecture initiatives, technical mentorship, performance engineering, observability, deep systems debugging, low-level system and OS internals, multi-threading, process scheduling, NUMA-aware memory allocation, lock-free data structures, context switching, I/O stack tuning, kernel bypass, CPU/GPU affinity optimization","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":274800,"unitText":"YEAR"}}}]}