Autonomous Solutions-posted about 24 hours ago
Full-time • Mid Level
51-100 employees

At ASI, we are revolutionizing industries with state-of-the-art autonomous robotics solutions. Within the fields of agriculture, construction, landscaping, and logistics, we deliver technologies that enhance safety, productivity, and efficiency. With our core values of Simplicity, Safety, Transparency, Humility, Attention to Detail and Growth guiding everything we do, we're shaping the future of automation in dynamic markets. As an AI Systems Engineer, you will play an essential role in designing, integrating, and managing AI driven components within our Core AI Research team. You will ensure AI models, embedded systems, cloud services, and software applications work together smoothly and reliably. This role requires a multidisciplinary mindset, strong systems thinking, and the ability to collaborate across engineering teams to bring intelligent features to life in real world environments.

  • Design system level frameworks that allow AI models to interact seamlessly with software, hardware, and cloud components.
  • Integrate machine learning models into production systems, ensuring performance, reliability, and maintainability.
  • Oversee the lifecycle of AI features including updates, security, monitoring, and scaling across deployments.
  • Collaborate closely with data scientists, robotics engineers, and software developers to deliver cohesive and efficient AI enabled systems.
  • Evaluate system level risks, dependencies, and performance impacts when introducing new AI capabilities.
  • Document system architecture, integration requirements, and operational processes.
  • Ensure ethical considerations such as transparency and accountability are reflected in system design and implementation.
  • Stay current with emerging technologies, industry trends, and best practices in AI systems engineering.
  • Bachelor's degree in Computer Science, Engineering, or a related technical field.
  • 5+ years of experience in systems engineering, AI engineering, or integrating complex technical systems.
  • Proficiency in programming languages such as Python and Java.
  • Strong understanding of machine learning principles, data modeling, and model deployment workflows.
  • Experience with system integration, cloud technologies, and distributed architectures.
  • Background working with tools like Jama, Jira, Doors, Requisite-Pro, Polarion SVN, and ANSYS.
  • Familiarity with security, monitoring, and lifecycle management of AI powered systems.
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