We are seeking a highly motivated and experienced AI/RL Software Engineer to join our team.
The ideal candidate will have a strong background in Python programming and a deep understanding of machine learning and reinforcement learning techniques.
Practical experience integrating Large Language Models (LLMs) and coordinating modular agents using Message Control Protocol (MCP) is required.
Responsibilities include developing novel Reinforcement Learning algorithms to solve complex, real-world problems.
The engineer will integrate LLMs to enhance agent reasoning, threat intelligence, or human-machine interactions.
Implementing and extending MCP to enable coordinated behavior across modular AI components or multi-agent systems is essential.
Prototyping new methods and helping transition successful prototypes into deployed solutions is part of the role.
Conducting thorough evaluations of model performance using appropriate experimental design and statistical analysis is expected.
Writing clean, maintainable, and well-documented code is crucial.
Troubleshooting and debugging complex software issues will be part of the daily tasks.
Participation in code reviews and ensuring the code quality of the team is required.
Requirements:
A Master’s or Ph.D. degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience is necessary.
Strong proficiency in Python programming language and experience with popular machine learning libraries is required.
Experience with reinforcement learning, specifically with OpenAI Gym, is essential.
Knowledge of CyberSecurity principles, tools, and techniques is needed.
Experience with container-based environments is required.
Exceptional analytical, conceptual, and problem-solving abilities are necessary.
Excellent oral presentation and technical writing skills in English are required.
The ability to work independently as well as part of a team is essential.
Motivated and self-driving personnel are preferred.
Benefits:
Highly competitive salary reviewed upwards on a regular basis is offered.
Working from home is encouraged, as performance is valued over location.
Participation in state-of-the-art projects and tech challenges, as well as large-scale projects, is available.
Opportunities for personal and professional development amongst industry experts and talented individuals are provided.
Continuous learning with access to broad resources is supported.
An onboarding plan and training are provided to ensure a smooth induction into the role.
Equipment support is available to ensure all necessary tools for effective and efficient work.
There is no dress code, allowing for maximum comfort while working.
