Fluent
Skills: Python, SQL, AWS, CI/CD
We are seeking a Senior MLOps Engineer based in Canada to join our data and machine learning team. This role will co-own MLOps practices at Fluent(https://himalayas.app/companies/fluent) Media and establish standards for model deployment, serving, scaling and infrastructure efficiency. Working with ML scientists, Data Engineering and Product, this engineer will ensure models support accurate ad selection through reliable production systems at an optimal cost to serve.
What You’ll Do
Partner with ML scientists to operationalize models in Databricks and AWS. Build, monitor and optimize automated pipelines for training, testing and deployment. Establish standards for model versioning, automated testing, release controls and performance monitoring. Design and scale model-serving infrastructure to meet latency, reliability and cost requirements. Lead investigations and resolve complex production issues across the ML lifecycle. Document repeatable workflows, review designs and code, and mentor colleagues in MLOps best practices. Create and maintain dashboards to track model performance, reliability and infrastructure cost.
Requirements
Strong experience with Databricks (preferred) and AWS-based ML workflows. Proficiency with Python, SQL, PySpark and related ML and data engineering tools. Experience with ML lifecycle management tools such as MLflow and Delta Live Tables. Proven ownership of architecture and operations for real-time, low-latency relevance models and serving endpoints. Hands-on experience with CI/CD, automated testing and monitoring systems. Ability to independently resolve production challenges and collaborate with ML scientists, engineers and Product. Experience reviewing pull requests, establishing engineering standards and mentoring colleagues.
Nice-to-Haves
Knowledge of data governance, security, and compliance in cloud environments. Familiarity with model observability and explainability frameworks. Experience with stream p …truncated… articipating in recrea…
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