Were seeking a senior ML engineer with strong expertise in large language models and agent-based systems to build the core reasoning and simulation capabilities behind a future platform for agentic voice experiences. You will work on advancing how LLMs plan adapt and evaluate actions in realistic environments contributing to the development of reliable and trustworthy AI work will focus on developing robust infrastructure and tooling for training simulation and evaluation of agentic LLMs. Youll design and run experiments in simulated environments build scalable evaluation pipelines and help integrate agent behaviors across client and backend systems. This role is an opportunity to push the boundaries of reasoning adaptive behavior and platform architecture for agent-based will collaborate closely with ML scientists applied researchers and product engineers to transform early research into deployable systems. Together we will shape a platform that empowers developers and end-users to build rich voice-driven AI experiences.
Bachelors degree in Computer Science Machine Learning or related quantitative field with 4 years of relevant industry experience
Strong skills in Python (preferred) and at least one other programming language
Proven experience in ML engineering including system design training pipelines and deployment workflows
Deep understanding of agent-based simulation agentic RAG systems and LLM evaluation methodologies
Ability to balance long-term platform vision with pragmatic short-term delivery in fast-paced environments
Experience deploying LLM models in research or production contexts
Knowledge of adaptive feedback loops reinforcement learning or interactive agent design
Familiarity with client-backend integration for AI-driven applications
MS or PhD in Computer Science Machine Learning or a related field
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