Senior/Principal Machine Learning Engineer
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The role
Lead the design and implementation of core ML systems powering AI agents in production, covering problem framing, data strategy, deployment, monitoring, and continuous improvement.
Own frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops to ensure scalable and enterprise-ready solutions.
Collaborate closely with software engineers, product managers, and data scientists to deeply integrate agents into the platform and workflows.
Remain hands-on with emerging agentic architectures while applying rigorous engineering judgment to build reliable, explainable systems at global scale.
Mentor and lead ML Engineering teams, shepherd development lifecycles, sprint planning, and foster a culture of collaboration, transparency, and innovation.
Stay current with AI advances in LLMs, RAG, and autonomous agents, and solve ambiguous problems in ways that deliver measurable impact and reliability.
Own frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops to ensure scalable and enterprise-ready solutions.
Collaborate closely with software engineers, product managers, and data scientists to deeply integrate agents into the platform and workflows.
Remain hands-on with emerging agentic architectures while applying rigorous engineering judgment to build reliable, explainable systems at global scale.
Mentor and lead ML Engineering teams, shepherd development lifecycles, sprint planning, and foster a culture of collaboration, transparency, and innovation.
Stay current with AI advances in LLMs, RAG, and autonomous agents, and solve ambiguous problems in ways that deliver measurable impact and reliability.
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