Research Engineer in RL

Key Skills

Algorithms, C# Programming, C++, Design, GPUs, Keras software library, Machine learning techniques, MLflow, MLOps tools, Pandas, Python Programming, PyTorch, Scikit-learn, TensorFlow, XGBoost

Job Description

As a RE in RL you’ll be both part of the Engineering team in Berlin and part of a project-focused cross-office team that has to deliver innovative AI technologies to a client. Your wisdom will be called upon for understanding business issues, identifying and developing the right AI and, specifically, RL technologies to solve them and bringing their answers to market. REs are involved at every step of the project life cycle, including providing technical expertise and establishing projects before sales, driving R&D for POCs, developing MVPs, and ensuring continuous improvement and maintenance for industrialized solutions.

The RL Engineer must accomplish the following:

• Develop novel algorithms and research ideas in fields such as RL and operational research with ML.
• Design and implement algorithms to best leverage modern hardware and distributed computing systems (CPUs, GPUs, TPUs, Cloud, etc.).
• Collaborate with the Research team to turn concept work into actionable content.
• Report and present experimental results and research findings clearly and efficiently, both internally and externally, orally and in writing in English.
• Upon request, collaborate with the business development team in their pre-sales activities, including but not limited to presenting the company to new prospective clients, and representing InstaDeep in conferences/events.

Who you are:

• You have created, trained, validated, benchmarked, and monitored ML and RL algorithms.
• You have learned how to use an extensive data frameworks and RL frameworks to create the pipelines needed to feed models with the appropriate data.
• You have a solid understanding of software development, data engineering, ML, and RL principles.
• You can clearly explain complex outcomes to a wide range of audiences.
• You know how to work in a team.
• You deeply understand data science and statistical methods, tools, and algorithms, such as RLLib, CleanRL, SB3, Scikit-Learn, TensorFlow, PyTorch, Jax, XGBoost, Pandas, MLFlow, or similar MLOps frameworks.

Requirements:

• S./Ph.D. degree in Computer Science, Operational Research, Reinforcement learning or related field.
• Experience in developing and debugging in Python. C/C++ or similar languages are a plus.
• Experience using deep learning frameworks such as Jax, PyTorch, Tensorflow and/or Keras.
• Proficiency with Git workflow or similar development with best coding practices.
• Research and software engineer experience demonstrated via contributions to open source, work experience or coding competitions.
• Excellent communication skills and collaboration with researchers and developers.
• Excellent English skills. German fluency is a plus.
• Professional experience in AI or similar fields is a plus.
• Some background in Electrical Engineering is a plus.
• By applying you confirm you can demonstrate that you have the right to work in Germany.