Senior Machine Learning Engineer at Talan

on-site · full-time · Visa sponsorship

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Responsibilities:
- Design, build and deploy production ML models and services on Google Cloud Platform (Vertex AI preferred).
- Lead development of scalable ML pipelines for ingestion, preprocessing, training and inference.
- Implement model lifecycle practices using MLflow and DVC (versioning, reproducibility, experiments).
- Containerize models with Docker and deploy/operate them on Kubernetes clusters.
- Collaborate with DevOps and Data Engineering to build CI/CD pipelines (GitLab) and automated deployments.
- Monitor, optimize and improve model performance, reliability and observability in production.
- Contribute to architectural decisions, standards and best practices for MLOps; mentor junior engineers.

Requirements:
- Advanced Python proficiency and strong software engineering practices.
- Proven experience deploying ML models into production environments on GCP (Vertex AI a plus).
- Hands-on experience with Docker and Kubernetes for containerized ML workloads.
- Practical knowledge of ML lifecycle tools (MLflow, DVC) and CI/CD (GitLab CI/CD preferred).
- Experience working in Agile/SCRUM teams and collaborating with cross-functional stakeholders.
- Professional working proficiency in Spanish and English.
- Nice to have: familiarity with R, large-scale data ecosystems and infrastructure-as-code tooling.