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Applied Intuition

Software Engineer

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Description

You will design, implement, and deploy software and machine learning components for behavior prediction and environmental interactions. You will build scalable inference, decision-making, and data-processing systems; transform logs into training datasets; evaluate model performance; refine estimation and planning algorithms; and maintain production-quality tools, libraries, testing, visualization, and workflow automation.

Responsibilities

  • Design, implement, and deploy software and machine learning components for behavior prediction and environmental interactions
  • Build scalable software for inference and decision-making in dynamic environments
  • Build and optimize pipelines for time-series and sensor data
  • Transform raw logs into structured datasets for modeling and forecasting
  • Develop testing and evaluation frameworks in simulated environments
  • Measure model accuracy and robustness against ground-truth data
  • Implement and refine state-estimation and decision-planning algorithms
  • Apply generative and deep learning methods to uncertainty modeling
  • Integrate models into low-latency production systems
  • Develop tools and infrastructure for visualization, experiment tracking, and continuous model delivery
  • Maintain modular code and rigorous testing strategies

Requirements

  • Bachelor's degree or foreign equivalent in Computer Science or a related field
  • One year of relevant experience
  • Python
  • Go or C++
  • Scalable software systems and data-intensive pipelines
  • Deep learning frameworks
  • Data modeling
  • SQL
  • Git
  • Deep neural networks, generative models, or reinforcement learning
  • Cloud infrastructure
  • Containerization
  • Software-service orchestration tools

Benefits

  • Equity

Skills

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See also

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