Edge AI/ML Engineering Director - Embedded Systems
Honeywell
Atlanta (GA)
On-site
USD 120,000 - 150,000
Full time
14 days+
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Job summary
Honeywell is looking for a hands-on lead in Atlanta, Georgia, specializing in Edge AI deployment. The role focuses on optimizing and deploying AI models at the edge, requiring deep expertise in embedded AI and a strong background in GPUs and MLOps. Ideal candidates will have a passion for innovation, along with strong problem-solving skills and experience in AI application deployment within embedded systems. This position provides opportunities to drive cutting-edge AI solutions and work collaboratively in dynamic environments.
Qualifications
Proven experience in embedded AI with hands-on expertise in GPU or AI accelerator deployment.
Strong skills in edge model optimization and embedded system architecture.
Deep understanding of AI/machine learning algorithms and computer vision applications.
Experience building and managing MLOps pipelines for AI model deployment at the edge.
Excellent problem-solving skills and passion for innovation in embedded AI technologies.
Responsibilities
Lead hands-on development and deployment of Edge AI solutions with a focus on model optimization and performance on embedded platforms.
Design and implement robust MLOps pipelines to support continuous integration and deployment of AI models at the edge.
Collaborate with cross-functional teams to integrate AI applications into embedded systems using GPUs and AI accelerators.
Provide technical leadership and mentorship in embedded AI, system architecture, and AI deployment strategies.
Drive innovation and problem-solving initiatives to enhance AI capabilities and deployment robustness on edge devices.
Skills
Embedded AI experience
GPU optimization
MLOps pipeline management
System architecture knowledge
Problem solving
Computer vision applications
Education
Advanced degree in Computer Science or Electrical Engineering
Job description
Honeywell is looking for a hands-on lead in Atlanta, Georgia, specializing in Edge AI deployment. The role focuses on optimizing and deploying AI models at the edge, requiring deep expertise in embedded AI and a strong background in GPUs and MLOps. Ideal candidates will have a passion for innovation, along with strong problem-solving skills and experience in AI application deployment within embedded systems. This position provides opportunities to drive cutting-edge AI solutions and work collaboratively in dynamic environments.