Altera
Altera
.**About the Role** We are seeking a Machine Learning Engineer to help drive the development, optimization and deployment of Altera FPGA Compiler. In this role, you will work at the intersection of **machine learning and compiler/toolchain development****Key Responsibilities** Develop, optimize, and deploy advanced machine learning technologies to enhance FPGA compiler performance, focusing on timing closure, resource utilization, and power efficiency.Evaluate and integrate emerging ML models (e.g., graph neural networks, reinforcement learning) and frameworks (e.g., PyTorch, TensorFlow) for compiler optimization tasks like placement, routing, and logic synthesis.Collaborate with customers, FPGA architects, and internal engineering teams to gather ML requirements, define success metrics, and deliver tailored, production-ready solutions.
factors including job location, job-related knowledge, skills, experiences, * Bachelor’s Degree or higher in Computer Science, Electrical Engineering, or a related field.* 10+optimization or ML systems engineering.* Experience with C++ and Python in production or research environments.**Preferred Qualifications*** Experience with Agile methodologies, GitHub Copilot or similar AI coding assistants, and high-performance computing environments.* Familiarity with edge AI inference on FPGAs and neuro-symbolic AI techniques.**Minimum Qualifications**
years of experience in machine learning development, model Strong communication skills for cross-functional collaboration and presenting results at conferences like DAC or FPGA World. #J-18808-Ljbffr
.**About the Role** We are seeking a Machine Learning Engineer to help drive the development, optimization and deployment of Altera FPGA Compiler. In this role, you will work at the intersection of **machine learning and compiler/toolchain development****Key Responsibilities** Develop, optimize, and deploy advanced machine learning technologies to enhance FPGA compiler performance, focusing on timing closure, resource utilization, and power efficiency.Evaluate and integrate emerging ML models (e.g., graph neural networks, reinforcement learning) and frameworks (e.g., PyTorch, TensorFlow) for compiler optimization tasks like placement, routing, and logic synthesis.Collaborate with customers, FPGA architects, and internal engineering teams to gather ML requirements, define success metrics, and deliver tailored, production-ready solutions.
factors including job location, job-related knowledge, skills, experiences, * Bachelor’s Degree or higher in Computer Science, Electrical Engineering, or a related field.* 10+optimization or ML systems engineering.* Experience with C++ and Python in production or research environments.**Preferred Qualifications*** Experience with Agile methodologies, GitHub Copilot or similar AI coding assistants, and high-performance computing environments.* Familiarity with edge AI inference on FPGAs and neuro-symbolic AI techniques.**Minimum Qualifications**
years of experience in machine learning development, model Strong communication skills for cross-functional collaboration and presenting results at conferences like DAC or FPGA World. #J-18808-Ljbffr