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Design and develop cycle approximate/Loosly timed C++/SystemC models for Cadence's IPs like PCIe controller, etc for use in early SW development ,architectural exploration and performance analysis at different levels - subsystem and SoC level.
- Design and develop protocol specific functional models for various Cadence's interface IPs like PCIe,UCIe,CXL,USB,Ethernet,UFS,DP, etc
- Interact with IP designers and architects to understand various IP design/implementation specification and behavior
- Participate in defining traffic patterns, tools and methodology based on the model to help identify functional issues and performance bottlenecks
- Documentation of design specifications, implementation details, FAQ's, application notes, etc
Experience in high performance SOC architecture with focus on system-level trade-offs
- Development of functional and behavioral (loosly timed)/(cycle-level) models using C++/SystemC/TLM2
- Experience in using RTL/UVM System Verilog simulation environments for model validation
- Experience in creating workloads for different SoC components at required levels of abstraction
- Knowledge of scripting languages (python, perl)
- Excellent communication skills and ability to work in a team spread over multiple time-zones
- BS/MS degree in Computer Science or Electrical Engineering, or equivalent practical experience(2-3yrs)
Job ID: 145003609
Skills:
snowflake , Hadoop, Cloudformation, Apache Spark, Kafka, Sql, ELT, Apache Airflow, Kinesis, Terraform, Databricks, Python, Etl, AWS
Skills:
Java, Agile Methodologies, Cloud Technologies, Python, database querying languages, modern front-end technologies, AI frameworks
Skills:
Java, Agile Methodologies, Cloud Technologies, Python, database querying languages, modern front-end technologies, AI frameworks
Skills:
Git, Bdd, Tdd, Linux System Administration, MongoDB, Devops Tools, Python, Sql, environment management, network fundamentals
Skills:
Rabbitmq, Computer Vision, Tensorflow, Opencv, MLops, Pytorch, Gcp, Git, JIRA, AWS, Python, Kubernetes, Azure, Docker, Apache Kafka, Jenkins, Nlp, DVC, ML infrastructure, model registry, GitLab CI, experiment tracking, GitHub Actions, infrastructure-as-code, MLflow, applied AI, HuggingFace Transformers, Weights Biases