Junior System Modeling

Unconventional AI
Palo Alto
Workplace: RemoteFull timeFunction: OtherEducation: bachelorsSkills: ["Problem-solving","Collaboration","Attention to detail"]

A hands-on, entry-level lab role focused on building and optimizing GPU-accelerated simulators for ML on analog/unconventional hardware. You will collaborate with senior engineers to integrate physics-based models into PyTorch, extend the end-to-end simulation environment, and help track experiments, enabling cross-layer optimization and rapid iteration on energy-efficient AI compute.

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FursaFursa
Unconventional AI
Unconventional AI
5 months ago

Junior System Modeling

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live

Job Summary

A hands-on, entry-level lab role focused on building and optimizing GPU-accelerated simulators for ML on analog/unconventional hardware. You will collaborate with senior engineers to integrate physics-based models into PyTorch, extend the end-to-end simulation environment, and help track experiments, enabling cross-layer optimization and rapid iteration on energy-efficient AI compute.
Location: Palo Alto
Workplace: Remote
Employment Type: Full time
Seniority: Entry level

Key Responsibilities

  • •Contribute to the implementation and optimization of GPU-accelerated simulators for ML on analog/unconventional hardware, focusing on specific modules and features within PyTorch.
  • •Assist in integrating physics-based device and system models into the PyTorch simulation environment to expose early algorithm–hardware tradeoffs and enable cross-layer optimization.
  • •Support the maintenance and extension of the unified end-to-end simulation environment, linking theory, algorithms, and device models and ensuring alignment between high-level and near-physical simulators.
  • •Help implement and adhere to robust experiment tracking protocols to ensure simulation results, configurations, and non-idealities are reproducible and auditable.
  • •Collaborate with Algorithms and Hardware teams to gather requirements and ensure the modeling environment meets their needs for high-level algorithm development and lower-level hardware verification.

Key Requirements

  • •Strong Systems Foundation: A BS, MS, or PhD in Computer Science, Electrical Engineering, or a related technical field with deep understanding of computer architecture and operating systems.
  • •Coding Proficiency: Strong skills in C++ and Python; comfortable writing performance-critical code.
  • •AI/ML Exposure: Basic familiarity with the internals of deep learning frameworks and common model architectures.
  • •Mathematical Intuition: Solid grasp of linear algebra and calculus for understanding neural dynamics and hardware optimizations.
  • •First Principles Mindset: Enjoy digging into why things work and challenge conventional software best practices to improve efficiency.
Experience:AIMLHPC
Education:Bachelor's in Computer ScienceUnknown
Skills:Problem-solvingCollaborationAttention to detail
Languages:English
Tech Stack:C++PythonPyTorchLLVMMLIRTritonCUDA

Company Brief

Unconventional AI
Builds customizable AI copilots and fine-tuned large language model solutions to help teams automate workflows, surface actionable insights, and integrate generative AI into business processes across products and operations.
Industry: AI & Machine Learning
Company Size: Small (11 to 50 employees)
Growth: Early Stage Startup
Funding: Seed
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