Want to challenge your machine learning skills to explore the new frontier of Human-in-the-Loop training? We're looking for an ML developer to do just that!
You're a genuine, generous and generative individual and want to join the ranks of our team of seasoned professionals to work on the future of human - machine interaction? Let's talk!
As a member of our team, you will apply rigorous critical thinking and a great dose of creativity to engineer unique solutions. You will need to work with people from diverse backgrounds, ranging from research academics to game developers in order to pave the future of human/machine collaboration.
Knowledgeable of AI standards: You have extensive experience using leading Machine Learning libraries and platforms like TensorFlow, PyTorch and Keras. You know OpenAI Gym inside out. You probably have a Masters degree in the fields of Computer Sciences, Mathematics, Statistics or other data-rich domains, or, have an equivalent level of expertise from Industry experience. Knowledge modeling human behaviour and doing Reinforcement Learning would be awesome.
Intellectually curious: you absorb new knowledge every day while always being on the lookout for new challenges for their learning opportunities. You don’t limit yourself to the bounds of your role or even of the company. You understand that knowledge, challenges and feedback can be found and come from everywhere.
Autonomous: you are proactive and self-driven. You are capable to take a high level goal and create your own plan to reach it. You take ownership, don’t require follow-up and are accountable to your results, whatever they might be.
Develop AI agents as well as the environments in which they operate, understanding the mutual influence environment and agents have on each other.
Improve the function of the team you are a part of, either through individual achievement or through leadership; you improve the organization too.
Maintain rich, thoughtful, candid communication with your peers in order to ensure the very best results.
Gather, acknowledge, and respond to internal feedback, adjusting design and technological choices as necessary.
Use quality work procedures that set a good example for others when implementing your solutions.