Research Engineer - Embodied AI/Robotics

1 Month ago • 1-4 Years • Artificial Intelligence • $98,300 PA - $208,800 PA

Job Summary

Job Description

This Research Engineer role at Microsoft Research focuses on developing infrastructure for embodied AI systems. Responsibilities include creating data pipelines, running benchmarks, evaluating algorithms (including post-training of Robotic Foundation Models and Reinforcement Learning frameworks), and integrating/deploying models onto robots (simulation and hardware). The ideal candidate possesses strong machine learning engineering skills, experience with deep learning frameworks (PyTorch, TensorFlow, etc.), and proficiency in Python/C++. The role demands expertise in designing, deploying, and managing ML workflows on cloud platforms and a deep understanding of state-of-the-art deep reinforcement learning approaches.
Must have:
  • Deep learning model implementation & evaluation
  • Machine learning engineering experience
  • Proficiency in Python
  • Software design & implementation skills
  • Experience with deep learning frameworks
Good to have:
  • Proficiency in C++
  • Experience with PyTorch/TensorFlow/JAX
  • Deep reinforcement learning understanding
  • Robotics/autonomous vehicles experience
  • Cloud platform experience
Perks:
  • Industry leading healthcare
  • Educational resources
  • Discounts on products and services
  • Savings and investments
  • Maternity and paternity leave
  • Generous time away
  • Giving programs
  • Networking opportunities

Job Details

Overview

Microsoft Research Accelerator works with the world's best researchers, moving with the current of technology as it rapidly evolves. Together we share the motivation to seek innovative solutions to the world's toughest challenges and improve the lives of people everywhere.  

 

We are looking for a Research Engineer who is passionate about developing new systems and transforming the latest machine learning models from concepts into reality. In this role you will drive the development of infrastructure for supporting demonstrations and evaluation of Embodied Artificial Intelligence (AI) systems. This includes creating pipelines for collecting data, running benchmarks, and evaluating embodied AI algorithms. Some examples of this work include the post-training of Robotic Foundation Models and the design of Reinforcement Learning frameworks. Additional duties include integrating and deploying these models onto robot systems both in simulation and hardware platforms.

 

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Qualifications

Required Qualifications

  • Bachelor's Degree in Computer Science, Mathematics, or Engineering or related field AND 2+ industry-level (research) software engineering experience
    • OR Master's Degree Computer Science, Mathematics, or Engineering, or related field AND 1+ year(s) related experience
    • OR Doctorate in Computer Science, Mathematics, or Engineering, or related field
    • OR equivalent experience.
  • Hands-on experience in implementing, evaluating, and/or applying deep learning models using deep learning frameworks.
  • Demonstrated track record of machine learning engineering as part of a team.
  • Software design and implementation skills with an object-oriented programming language, such as Python.

Preferred Qualifications

  • Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  • Understanding of state-of-the-art deep reinforcement learning approaches.
  • Experience in solving deep research challenges relevant to practical applications in robotics, autonomous vehicles, gaming or similar application areas.
  • Experience in designing, deploying, and managing machine learning workflows on cloud platforms.

Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $127,200 - $208,800 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications for the role until January 15, 2025.

 

 

#Research

Responsibilities

  • Lead the design and implementation of machine learning systems as part of an ambitious, high-impact research agenda, within the context of a highly collaborative research culture throughout all stages of the research and development cycle. This includes, for example, development of highly scalable research infrastructure, data handling, model development and resource management. 
  • Work with engineering teams to perform end to end integration of ML platforms onto robotic systems  
  • Analyze and refine training datasets for robotic and AI applications 
  • Developing benchmarks and evaluation procedures for state of the art models. 
  • Stay up-to-date with the latest advancements in machine learning and related fields. 
  • Collaborate with cross-functional teams to understand requirements and deliver high-quality solutions 
  • Instill best practices for software development and documentation.
  • Embody our and .
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Industry leading healthcare
Educational resources
Discounts on products and services
Savings and investments
Maternity and paternity leave
Generous time away
Giving programs
Opportunities to network and connect

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