Machine Learning Simulation Engineer

Cupertino, CA
  • Job Code
    200283703
Summary

Summary

Posted: Aug 31, 2021

Role Number:200283703

Deliver innovative solutions at the intersection of machine learning (ML) and simulation in the context of autonomous systems deve...Summary

Summary

Posted: Aug 31, 2021

Role Number:200283703

Deliver innovative solutions at the intersection of machine learning (ML) and simulation in the context of autonomous systems development.

Key Qualifications

  • Strong proficiency in C++, Python, and best practices in object-oriented design. Familiarity with PyTorch, OpenAI Gym, and RLlib toolkits.
  • Expertise in statistical modeling, parameter optimization, and system identification techniques.
  • Experience benchmarking and debugging complex software systems.
  • Ability to work synergically and cross-functionally in large-scale software development projects.
  • At ease with Git, Docker, and UNIX-based software development.

Description

A successful applicant is expected to undertake software projects for the development and improvement of simulation tools in support of ML models and methods, as well as integrating novel and existing ML results into a shared simulation ecosystem to increase its capabilities.

RESPONSIBILITIES INCLUDE BUT ARE NOT LIMITED TO:
- Maintaining a strong relationship with other teams to integrate new algorithms and models as they become available.
- Developing and maintaining appropriate software interfaces and improving runtime performance of our simulation environment in support of Reinforcement Learning and other types of ML use cases.
- Integrating existing, and possibly also build new, data-driven models for the simulation of realistic agent behaviors and sensor outputs, as well as synthetic scenario generation.
- Improving performance and maintaining data ingestion pipelines for playback- based simulation workflows.
- Expectations also include hands-on experience with data logs from real-world experiments, identification of sim-to-real gaps that might impact our ML models, and implementation of appropriate fixes and mitigations.

Education & Experience

MS in engineering (ML, robotics) and 2+ years of industry experience or equivalent industry experience.

Additional Requirements

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