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Machine Learning Engineer

Location
Bangalore, India

Avesha is a Boston based seed funded startup focused on building a scalable platform to accelerate the performance of applications across hybrid, edge and multi-cloud by creating seamless end-to-end intelligent application overlay network. We are looking for a highly skilled developer who has experience in building Machine Learning systems to join our growing team in Bangalore.

 

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.