Software Development

EnliteAI GmbH

11-50

Austria

Apply cutting-edge research in Artificial Intelligence and Reinforcement Learning (RL) to real-world optimization and decision problems. Work on high-impact applications such as next-generation smart power grids.

## Tasks

*   Assume responsibility in international and national research projects
*   Contribute building blocks and methodology based on our open-source framework Maze, focused on simulation-based RL, together with an exceptional team of Research Scientists, Machine Learning Engineers and Infrastructure Experts
*   Analyze industry-related optimization and decision problems and translate them into Machine Learning systems (covering the complete development cycle from simulation engineering up to agent development, training and deployment)
*   Design and implement proof of concepts, develop prototypes in Python and PyTorch for both RL-ready simulations (environments) as well as RL agents
*   Review state-of-the-art literature and judge its relevance for practical applicability

## Requirements

*   Strong background in the field of RL and related Machine Learning disciplines
*   Excellent Python programming skills, knowledge of PyTorch and a wide range of Machine Learning methods
*   Passionate about all things, AI, Machine Learning and Data Science
*   Self-driven problem solver who enjoys coding as much as tinkering
*   Ability to work independently as well as part of a team
*   Degree in computer science (MSc or Ph.D.) or in a similar field
*   Valid work permit for Austria

## Benefits

*   Enthusiastic, research-driven team with rich expertise in Reinforcement Learning and Computer Vision as well as distributed training, data engineering, ML ops and cloud architecture
*   Working with the latest technologies at the interface between research and industry (enliteAI is an ELISE EU research network Organizing Node)
*   Flexible work models: Remote work, an office in Vienna's 1st district and minimal core hours
*   Budget and time allotment for the pursuit of individual R&D projects, training or conference participations

Employee

Professional / Experienced

<p>Apply cutting-edge research in Artificial Intelligence and Reinforcement Learning (RL) to real-world optimization and decision problems. Work on high-impact applications such as next-generation smart power grids.</p>
<h2 id="tasks">Tasks</h2>
<ul>
<li>Assume responsibility in international and national research projects</li>
<li>Contribute building blocks and methodology based on our open-source framework Maze, focused on simulation-based RL, together with an exceptional team of Research Scientists, Machine Learning Engineers and Infrastructure Experts</li>
<li>Analyze industry-related optimization and decision problems and translate them into Machine Learning systems (covering the complete development cycle from simulation engineering up to agent development, training and deployment)</li>
<li>Design and implement proof of concepts, develop prototypes in Python and PyTorch for both RL-ready simulations (environments) as well as RL agents</li>
<li>Review state-of-the-art literature and judge its relevance for practical applicability</li>
</ul>
<h2 id="requirements">Requirements</h2>
<ul>
<li>Strong background in the field of RL and related Machine Learning disciplines</li>
<li>Excellent Python programming skills, knowledge of PyTorch and a wide range of Machine Learning methods</li>
<li>Passionate about all things, AI, Machine Learning and Data Science</li>
<li>Self-driven problem solver who enjoys coding as much as tinkering</li>
<li>Ability to work independently as well as part of a team</li>
<li>Degree in computer science (MSc or Ph.D.) or in a similar field</li>
<li>Valid work permit for Austria</li>
</ul>
<h2 id="benefits">Benefits</h2>
<ul>
<li>Enthusiastic, research-driven team with rich expertise in Reinforcement Learning and Computer Vision as well as distributed training, data engineering, ML ops and cloud architecture</li>
<li>Working with the latest technologies at the interface between research and industry (enliteAI is an ELISE EU research network Organizing Node)</li>
<li>Flexible work models: Remote work, an office in Vienna&#39;s 1st district and minimal core hours</li>
<li>Budget and time allotment for the pursuit of individual R&amp;D projects, training or conference participations</li>
</ul>


Researcher in application-oriented Reinforcement Learning

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