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Research Analyst II
Ref No.: 20-02435
Location: Redmond, Washington
Tailored Management is seeking a candidate to join the world's largest social media network who enables over a billion users to openly connect with friends and family, share content, and explore the world. You'll have the opportunity to work with great people, tackle big challenges, and make a real impact – while being your unique, authentic, self at work!

Research Analyst II
Redmond, WA
Health Benefits + PTO


At Reality Labs, our goal is to explore, innovate and design Client interfaces and hardware for the next generation of virtual, augmented, and mixed reality experiences. We are driving research towards a vision of an always-on AR device that can provide contextually relevant assistance across a range of complex, dynamic, real-world tasks in natural environments. To this end, we are looking for a reinforcement learning (RL) and/or optimal control research analyst who can accelerate the team's research.

The role will include implementing baseline published reinforcement learning, inverse reinforcement learning, deep and cooperative reinforcement learning algorithms; collaboration and experimentation on Client algorithms and models with researchers; collaboration with engineers to deploy models in AR/VR prototypes; and other related work.

  • Minimum of 2 years' experience in scientific Python (e.g., numpy, scipy, pandas).
  • Experience with reinforcement-learning toolkits such as Gym and/or at least one deep learning toolkit (e.g., PyTorch or TensorFlow).
  • Experience in implementing RL/stats/Client methods from research papers.
  • Background in reinforcement learning, optimal control, dynamic programming, embodied AI, active/online learning, Markov decision processes, human-machine collaboration, or related fields.
  • Familiarity with multi-agent systems, meta-learning, and online learning methods.
  • Familiarity with 3D simulation engines such as Unity.
  • Required: BS in computer science, applied math/control, robotics, or a related field.
  • Preferred: MS in computer science, applied math/control, robotics, or a related field.