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Metro location, mid-level generalist ML role at a known global brand increases applicant competition.
ML and MLOps skills are transferable across industries but require specialized ML experience.
Explicit 3+ years plus required GCP/Vertex, Python, MLOps, Terraform and LLM experience increases filter strictness.
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Build, validate, and deploy machine learning models for business problems like churn, retention, and content classification affecting millions of users.
Develop production features for RAG and LLM systems on Google Cloud Vertex AI including retrieval, prompt engineering, and evaluation.
Contribute to ML architecture and design, maintain CI/CD pipelines, and collaborate with cross-functional teams including newsroom, marketing, and product stakeholders.
3+ years of hands-on data science or applied machine learning experience with production delivery.
Strong Python software engineering skills with testing, code review, and version control (Git).
Experience with Google Cloud Platform (GCP) including Vertex AI, BigQuery, Cloud Run, and Terraform for infrastructure as code.
Strong SQL skills and hands-on ML lifecycle experience including feature engineering, modeling, deployment, and monitoring.
Experienced working in end-to-end MLops environments with CI/CD, model monitoring, and drift detection expertise.
Practical knowledge of LLMs, generative AI including RAG, prompt engineering, and familiarity with advanced tooling like LangChain, Google ADK, Gemini, or Claude.
Capable of explaining complex technical solutions clearly to both technical and non-technical stakeholders in cross-functional agile teams.