Our Hardware Engineers at Synopsys are responsible for designing and developing cutting-edge semiconductor solutions. They work on intricate tasks such as chip architecture, circuit design, and verification to ensure the efficiency and reliability of semiconductor products. These engineers play a crucial role in advancing technology and enabling innovations in various industries.
\nYou are a dedicated engineer with a passion for analog and mixed-signal IC design, eager to push the boundaries of semiconductor technology. You thrive in environments where innovation, precision, and collaboration are key. Your technical expertise is matched by your curiosity and willingness to continuously learn, adapting to new challenges and technologies. You enjoy working hands-on, taking ownership of the design process from conception to silicon validation. With a keen eye for detail and a strong analytical mindset, you excel at optimizing performance and robustness in high-speed interfaces. You are comfortable navigating complex circuit architectures, and your experience allows you to anticipate issues and implement creative solutions. You value open communication and teamwork, working effectively with layout and lab teams in a multicultural setting. Your documentation skills ensure clarity and reproducibility throughout the design cycle. You are motivated by the opportunity to make a tangible impact on industry-leading products, and you seek growth not only in technical depth but also in architectural responsibility. Ultimately, you are a proactive contributor, ready to help Synopsys shape the next generation of high-speed analog solutions.
\nDesign, analyze, and optimize high-speed analog and mixed-signal circuits such as voltage regulators, DACs, AFE/DFE, TX drivers, serializers, and supporting blocks. Conduct detailed circuit behavior analysis, tuning performance and proposing improvements for power, speed, and robustness. Perform timing closure for small digital blocks using NanoTime, ensuring accurate integration with analog designs. Lead technical interactions with layout teams, guiding floorplanning, matching, and parasitic-aware design to achieve block specifications. Participate actively in design reviews, layout reviews, and silicon bring-up processes to ensure quality and reliability. Support lab characterization and debug, correlating simulation results with silicon measurements for optimal validation. Document architectures, design decisions, testbenches, simulation results, and silicon learnings to maintain clarity and foster knowledge sharing.
\nAdvance Synopsys' leadership in high-speed SerDes IP and analog interface technology. Enable the development of state-of-the-art products used across diverse industries, from data centers to automotive. Drive innovation in design methodologies, influencing future product architectures and performance standards. Enhance cross-functional collaboration, ensuring seamless integration between design, layout, and validation teams. Improve product robustness and yield through meticulous analysis, testing, and documentation. Accelerate time-to-market for cutting-edge chips by optimizing design cycles and validation processes. Contribute to a culture of continuous improvement and technical excellence within Synopsys' engineering community.
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\nThis role spans retrieval, matching, relevance, ad quality, fraud and abuse detection, content and intent understanding, foundation-models and its powered recommendation experiences. This role is focused on creating the scientific foundations that enable new monetization scenarios to scale with high quality, operational efficiency, and rapid iteration across evolving product surfaces.
\nThe ideal candidate will operate across multiple horizons: delivering measurable near-term product and business impact, while shaping the long-term architecture of next generation of Ads systems.
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\nDefine, drive and deliver multi-year technical strategy, and investment roadmap for large-scale recommender and decisioning systems across Ads.
\nLead the invention, incubation, and productionization of next-generation machine learning systems spanning large retrieval models, foundation-model-powered recommendation systems and agentic workflows.
\nDrive step-function improvements in relevance, user value, advertiser outcomes and system efficiency
\nInfluence senior leaders across product, engineering and partner science organizations on scientific direction, architecture, long-range capability building, and prioritization of major investments.
\nMentor scientists and engineers, elevate scientific rigor and technical standards across the organization, and help shape the next generation of applied science leadership.
\nQualifications:
\nBachelor’s Degree in Computer Science, Statistics, Electrical Engineering, Computer Engineering, or related field AND 15+ years of related experience in applied science, machine learning, recommender systems, information retrieval, ranking, optimization, or related areas OR Master’s Degree in a related field AND 12+ years of related experience OR Doctorate in a related field AND 10+ years of related experience OR equivalent experience.
\nDeep expertise in one or more of the following areas: retrieval, relevance, recommender systems, large-scale machine learning, trust and safety
\nProven track record of defining technical and scientific strategy for large-scale machine learning systems and delivering measurable product and business impact in production environments.
\nDemonstrated experience leading cross-organizational scientific initiatives and influencing technical direction across multiple teams, product surfaces, or organizational boundaries.
\nStrong communication, technical leadership, and cross-functional collaboration skills, with the ability to connect deep scientific work to product, engineering, and business outcomes.
\nDemonstrated ability to operate effectively in ambiguous, fast-evolving technical spaces and convert emerging opportunities into scalable production direction.
\nExperience building foundation models for large-scale recommender systems
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