Senior/Principal Machine Learning Engineer
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The role
Design and build the core ML systems behind next-generation AI agents, shaping problem framing, data strategy, and model orchestration in production.
Own the end-to-end lifecycle from data collection and experimentation to deployment, monitoring, and continuous improvement.
Develop and evolve frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops.
Collaborate with software engineers, product managers, and data scientists to deeply embed agents into enterprise platforms with strong observability and reliability.
Apply state-of-the-art techniques and rigorous engineering practices to deliver scalable, explainable, and responsible AI at global scale.
Lead by example—mentoring teammates, guiding sprint planning, and promoting best practices in MLOps, testing, and performance assessment.
Own the end-to-end lifecycle from data collection and experimentation to deployment, monitoring, and continuous improvement.
Develop and evolve frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops.
Collaborate with software engineers, product managers, and data scientists to deeply embed agents into enterprise platforms with strong observability and reliability.
Apply state-of-the-art techniques and rigorous engineering practices to deliver scalable, explainable, and responsible AI at global scale.
Lead by example—mentoring teammates, guiding sprint planning, and promoting best practices in MLOps, testing, and performance assessment.
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