Work Location: WA - Redmond
Duration: +1 year with a possibility of extension or conversion.
Rate: $50-60/hr on W2
At Facebook Reality Labs, our goal is to explore, innovate and design novel 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 novel algorithms and models with researchers; collaboration with engineers to deploy models in AR/VR prototypes; and other related work.
* Experience with reinforcement-learning toolkits such as Gym, AI Habitat, AI2THOR
* Minimum of 2 years experience with at least one deep learning toolkit (e.g., PyTorch or TensorFlow).
* Experience implementing RL/stats/ML methods from research papers.
* Experience with distributed training, GPU management, hyperparameter optimization etc.
* Background in reinforcement learning, optimal control, dynamic programming, embodied artificial intelligence (AI), active/online learning, Markov decision processes, human–machine collaboration, or related fields.
* Familiarity with multi-agent systems, meta-learning, and online learning methods.
* 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.