Senior Machine Learning Engineer, Agentic
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Die Stelle
Design and build tools and workflows for agent development to enable rapid prototyping, define agents, and assemble toolchains with minimal overhead.
Create scalable platforms for experimentation, synthetic data generation, and multi-agent evaluation across diverse tasks and domains.
Develop feedback and optimization pipelines that blend automated metrics with human-in-the-loop signals to tune agent behavior.
Implement and scale optimization techniques such as Direct Preference Optimization (DPO), Proximal Policy Optimization (PPO), and reward modeling.
Launch and monitor fine-tuned models in production, with robust evaluation, rollback strategies, and observability.
Collaborate with applied AI/ML teams to translate state-of-the-art agentic reasoning, planning, and tool use into reliable systems.
Create scalable platforms for experimentation, synthetic data generation, and multi-agent evaluation across diverse tasks and domains.
Develop feedback and optimization pipelines that blend automated metrics with human-in-the-loop signals to tune agent behavior.
Implement and scale optimization techniques such as Direct Preference Optimization (DPO), Proximal Policy Optimization (PPO), and reward modeling.
Launch and monitor fine-tuned models in production, with robust evaluation, rollback strategies, and observability.
Collaborate with applied AI/ML teams to translate state-of-the-art agentic reasoning, planning, and tool use into reliable systems.
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