Requirements:

• Must have BS/MS degree in Computer Science or equivalent with solid understanding of fundamentals of algorithms, operating systems and networking.
• At Least 3+ years of experience in the machine learning software development life cycle.
• Experience with Reinforcement Learning.
• Solid understanding of basic Machine Learning and Deep Learning algorithms and Statistical methods.
• Experience with Machine Learning frameworks like Tensorflow and Pytorch using Python and/or C++.
• Experience with distributed Machine Learning frameworks and development and deployment of such systems using Kubernetes or Docker.
• Knowledge and experience with networking technologies and IP routing protocols is a plus.
• Excellent debugging skills of large scale distributed systems software and desire and ability to go under the hood to learn, optimize and debug.
• Good outstanding problem-solving and analytical skills with excellent written and oral communication skills.
• Working knowledge of cloud systems like AWS, Azure, GCP, etc.
• Ability to work in a self-directed manner across multiple teams in a fast paced setting.

Responsibilities:

• The software development engineer will design and develop reinforcement learning algorithms to solve problems in distributed network systems.
• Research latest developments and algorithms in RL/ML and document/present the findings and quickly prototype solutions.
• Work with other R&D engineers to analyze, implement, benchmark and test various algorithms.
• Own modules end to end through design, development, test and performance analysis in an iterative manner.
• Take prototype solutions and implement robust, production ready software.