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Mid-level AI role in a metro with broad MLOps and LLM requirements increases applicant competition.
ML engineering skills transfer across industries, though agency marketing experience gives moderate advantage.
Explicit 2+ years experience plus MLOps, Databricks, and production ML requirements create moderate hiring filters.
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Own the design, development, and maintenance of production-ready machine learning and generative AI pipelines including training, deployment, and monitoring.
Implement and uphold MLOps best practices such as experiment tracking, model versioning, and continuous evaluation to ensure scalable and reliable AI solutions.
Collaborate closely with clients and cross-functional teams to operationalize AI models across digital, analytics, and marketing platforms, ensuring integration and alignment with business objectives.
Bachelor’s degree in a relevant field or equivalent practical experience; Master’s degree preferred.
2+ years of professional experience in machine learning, data platforms, or AI systems, including hands-on deployment and operation of ML or generative AI models in production.
Strong proficiency with Python, SQL, object-oriented programming, and knowledge of Databricks.
Experience with MLOps practices including experiment tracking, model versioning, monitoring, and building data/model pipelines in distributed environments.
Experienced in operationalizing machine learning and generative AI systems with a focus on reliability, scalability, and production stability.
Comfortable working simultaneously with technical teams (data scientists, engineers) and explaining complex AI concepts to non-technical stakeholders and clients.
Background or familiarity with integrated marketing, digital agencies, consulting, or marketing technology platforms is preferred but not mandatory.