Senior Platform Engineer – MLops / Databricks at EROS Technologies Inc. | Torre
Senior Platform Engineer – MLops / Databricks
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EROS Technologies Inc.

Senior Platform Engineer – MLops / Databricks

EROS Technologies Inc.
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Full-time

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Remote (for Mexico residents)
Remote (for Brazil residents)
Remote (for Colombia residents)
Remote (for Argentina residents)
Posted about 2 months ago

Responsibilities

Role: Senior Platform Engineer – MLOps / Databricks. Location: Anywhere in LATAM - Remote. Key Responsibilities: - Design, implement, and maintain cloud-native platforms supporting AI and data workloads, with a focus on Databricks and AWS. - Build and manage scalable data pipelines to ingest, transform, and serve data for ML and analytics. - Develop Infrastructure-as-Code (IaC) solutions using CloudFormation and AWS CDK to ensure repeatable and secure deployments. - Collaborate with AI engineers, data engineers, and platform teams to improve performance, reliability, and cost efficiency of AI models in production. - Drive observability best practices, including monitoring, alerting, and logging across AI platforms. - Contribute to the design and evolution of AI platforms that support new ML frameworks, workflows, and data types. - Stay current with emerging tools and technologies and recommend improvements to platform architecture and operations. - Integrate AI models and Large Language Models (LLMs) into production systems, including Retrieval-Augmented Generation (RAG) architectures. Minimum Qualifications: - 7+ years of professional experience in software engineering and infrastructure engineering. - Extensive experience building and maintaining AI/ML infrastructure in production environments, including model deployment and lifecycle management. - Strong knowledge of AWS and Infrastructure-as-Code frameworks, ideally AWS CDK. - Expert-level coding skills in Node.js and Python, with experience developing APIs and backend services. - Proven experience with MLflow, including model registration, versioning, asset bundles, and model-serving workflows. - Hands-on experience with Databricks and modern data platform technologies. - Experience with CI/CD pipelines, containerization, and cloud-native architectures. - Strong understanding of MLOps best practices and AI platform engineering. Preferred Skills: - Databricks. - MLflow. - Python. - Node.js. - AWS CDK. - CloudFormation. - MLOps. - LLMs & RAG. - CI/CD. - Docker. - Kubernetes.
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