Machine Learning Engineer with Reinforcement Learning Expertise

As a Machine Learning Engineer at warmwind, you will push the boundaries of AI by developing innovative solutions that redefine how machines interact with software and the digital world. With a focus on reinforcement learning and cutting-edge approaches like token-based robotic interaction, you will design, implement, and optimize intelligent systems that drive our platform's evolution.

Your work will directly influence the next generation of AI, moving beyond traditional paradigms to create precision-driven, efficient, and scalable models that power warmwind's capabilities. By blending experimentation and practical application, you'll be instrumental in shaping the future of machine intelligence within our groundbreaking product.

Responsibilities

• Train and optimize models for virtual robotic control in dynamic environments
• Implement reinforcement learning strategies, including adversarial self-play and RLHF
• Develop scalable architectures for large-scale training on distributed clusters
• Collaborate on building a virtual training environment, including simulation pipelines
• Analyze performance metrics and iterate on model improvements, We operate in a dynamic startup environment where speed, efficiency, and innovation are key to achieving our goals and growing together. Our development process is based on rapid iterations, allowing us to quickly implement and test ideas to enhance our product and meet user needs.

What we offer:

• Innovation Opportunities: Work on cutting-edge technology and help shape the technical direction of our product.
• Impact: Your contributions will directly influence the user experience and the success of our platform.
• Startup Atmosphere: Flat hierarchies, direct communication, and a real opportunity to create something very big.
• Fair Compensation: Performance-based payment with the opportunity to participate in the growth through success.
• Flexible Work Conditions with Structure: We offer you high flexibility in shaping your workday-provided tasks and goals are met, you're free to design your workflow. At the same time, we value efficient collaboration during core working hours to move projects forward and facilitate quick discussions.

• Strong knowledge of reinforcement learning, neural network architectures, and optimization techniques
• Hands-on experience with large-scale distributed training on high-performance compute clusters (e.g., HPC systems, multi-GPU setups)
• Proficiency in Python and frameworks like PyTorch or TensorFlow
• Familiarity with real-time decision-making systems and continuous control tasks
• A strong understanding of AI research trends, with a focus on innovative approaches beyond LLMs
• Willingness to relocate to Jena, Germany, after an initial onboarding period and work on-site