Machine Learning Engineer (3 of 3)

Dollar General • Goodlettsville, TN

11d

About The Position

The Machine Learning Engineer optimizes and productionalizes machine learning systems to support scalable, low-latency business solutions. The role evaluates existing machine learning processes, uses statistical analysis to resolve data issues, and improves the accuracy and reliability of predictive automation. It helps increase delivery speed, code quality, and process efficiency in support of productionizing models. The engineer identifies production methods for automating model code deployment to operational production systems and implements infrastructure tools, code, and support services across multiple clouds, along with metrics and access to information.

Requirements

• Excellent coding and scripting skills, including Bash and Shell.
• Experience implementing large-scale cloud architectures using modern cloud-based container platforms (PaaS/SaaS).
• Knowledge of deploying ML pipelines using Azure ML and Databricks (MLFlow).
• Ability to test, build, and deploy ML models in production using an approach akin to DevOps, specifically for ML code and infrastructure, including Databricks.
• Knowledge of Azure cloud infrastructure and management tools for IT components, storage, networking, and caching.
• Experience with containerization, Docker, and Kubernetes.
• Bachelor’s degree in Computer Science, Data Science, Mathematics, or a related field.
• Minimum of four years of experience as a Machine Learning Engineer or equivalent experience in production ML systems.

Nice To Haves

• Master’s degree in Computational Linguistics, Data Analytics, or a related discipline.

Responsibilities

• Assess existing machine learning pipelines to identify problems and drive process improvement solutions.
• Identify bottlenecks in coding development and implementation, including code packaging, to reduce data science and engineering effort.
• Participate in planning initiatives related to delivery timelines, code quality, and process efficiency improvements.
• Execute improvement plans by defining coding standards and automating development and deployment processes across the organization.
• Perform daily operational tasks, including setting up development and production environments, monitoring metrics, and responding to incidents.
• Develop and maintain expertise in platform configuration management and troubleshooting.
• Deploy application components across appropriate environments using supported infrastructure and cloud technologies.
• Collaborate with Data Scientists, Data Engineers, and technical stakeholders to understand challenges related to machine learning coding and development processes.
• Translate business objectives into production-ready models and establish metrics to track performance and outcomes.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level