We are a next-gen cybernetics start-up backed by a few top-tier investors (led by NEA).
Our R&D blends robotics, machine learning, and high-fidelity simulation. We aim to push the boundaries of what intelligent systems are capable of achieving both autonomously and in collaboration with humans. We are building a developer-facing cloud-based platform that makes robots smarter, safer and human compatible.
You can expect to be part of something exciting at the contour of human knowledge.
About the Role:
As an AI Research Engineer, your primary responsibility will be to design and implement algorithms for generating human-interpretable skills. You will create machine learning (ML) pipelines for extracting hierarchical structures and represent them in human-readable formats. You will need to understand the vision and architectural decisions behind the existing code, this will help you learn and become very familiar with the code base and acquire an ability to develop features with minimal supervision while maintaining an ability to collaborate with fellow team members. You will have plenty of opportunities to apply tools in new and unique ways or design new algorithms as needed.
In this role, you will work directly on the core technology of our company. You will have opportunities to see the results of your work both in real and virtual worlds.
You are a self-motivated individual with a strong sense of ownership, urgency, and resiliency. You are open to learning new ways of doing things and good at build working relationships with existing team members. You are able to work with minimal direction and input, you are also able to document your work for projects via wiki or some other means of document tracking.
- 5+ years experience (previous work, publications, projects, classes, competitions etc.) in Reinforcement Learning (RL), supervised ML, and unsupervised ML algorithms.
- 5+ years experience with python ML libraries such as scikit-learn, PyTorch, Keras, gym etc.
- Solid understanding of (both theoretical and practical) the vanilla versions of traditional RL, supervised ML, and unsupervised ML algorithms such as Q-learning, actor-critic, classifiers, regressors, PCA, k-means etc.
- Ability to communicate your work effectively through documents, presentations, and reports to stakeholders.
- Experience in any of the followings:
- Explainable artificial intelligence (XAI).
- Behavior trees (BTs).
- Control systems background
- Robotics background
- Optimization background
- Experience with time series analysis.
A way to stand out from the crowd is to have a well-thought-out position on the topic:
“What are the major limitations of AI systems today and what are the practical ways to combat them?”
- Competitive salaries
- Significant stock
- Flexible schedule
- Freedom to make ground-breaking decisions
- Unlimited time off (we encourage 4+ weeks/year)
- “Exploration day” each week when you can research a topic of your choosing.
- Medical, dental, and vision coverage