Senior Machine Learning Developer
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El puesto
Line 1: Own the end-to-end lifecycle of machine learning models, from conception and implementation to automated testing, deployment, and monitoring.
Line 2: Improve model performance and system reliability to meet strict SLAs for large-scale training and low-latency inference.
Line 3: Maintain and evolve client-facing features powered by ML, ensuring robust, scalable production capabilities.
Line 4: Enable teams to adopt ML platforms, observability tools, and best practices that boost efficiency and service reliability.
Line 5: Collaborate with scientists and cross-functional partners to challenge approaches, optimize workflows, and guide architectural decisions.
Line 6: Build and evolve a modern tech stack including Python, AWS, Kubernetes, PyTorch, Terraform, Snowflake, observability tooling, and promote reusable internal tooling.
Line 2: Improve model performance and system reliability to meet strict SLAs for large-scale training and low-latency inference.
Line 3: Maintain and evolve client-facing features powered by ML, ensuring robust, scalable production capabilities.
Line 4: Enable teams to adopt ML platforms, observability tools, and best practices that boost efficiency and service reliability.
Line 5: Collaborate with scientists and cross-functional partners to challenge approaches, optimize workflows, and guide architectural decisions.
Line 6: Build and evolve a modern tech stack including Python, AWS, Kubernetes, PyTorch, Terraform, Snowflake, observability tooling, and promote reusable internal tooling.
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