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The Machine Learning Infrastructure Engineer will design and maintain scalable infrastructure for machine learning models, working alongside data scientists and engineers. Responsibilities include implementing infrastructure-as-code, deploying models efficiently, optimizing performance, and ensuring data security and integrity.

The Machine Learning Engineer/Applied Researcher will train and fine-tune Large Language Models, implement supervised fine-tuning techniques, collaborate with teams on experiments, optimize training pipelines, and document findings. The role requires expertise in modern ML practices and effective communication skills to convey technical concepts to various stakeholders.

The Platform Infrastructure Engineer will build, scale, and maintain multi-tenant, multi-cluster infrastructure on AWS EKS, automate infrastructure provisioning, and streamline deployment pipelines. They will leverage tools like ArgoCD and Terraform, manage GitOps workflows, and monitor GPUs, collaborating closely with developers and DevOps teams to enhance system reliability and performance.