Senior MLOps Engineer
emagine · Portugal · remote
Responsibilities
- Design, build, and maintain scalable MLOps and LLMOps infrastructure on GCP.
- Develop and manage ML pipelines using MLflow, ZenML, Kubeflow, and Vertex AI Pipelines.
- Manage containerized environments using Docker and Kubernetes.
- Automate infrastructure provisioning with Terraform.
- Build and maintain CI/CD pipelines for ML and GenAI applications using GitHub Actions.
- Design and orchestrate LLM and agentic workflows using LangGraph.
- Implement evaluation frameworks for LLMs, RAG systems, and AI agents.
- Monitor ML and GenAI applications, including model performance, drift, tracing, and observability.
- Develop scalable data processing pipelines using Dataflow and Apache Beam.
- Collaborate with Data Scientists and Engineering teams to deliver production-ready AI solutions.
- Provide technical guidance and promote MLOps and LLMOps best practices across the team.
Requirements- Strong professional experience in MLOps / LLMOps.
- Hands-on experience with GCP, particularly Vertex AI, Dataflow, and BigQuery.
- Strong knowledge of Terraform, Docker, and Kubernetes.
- Experience with Kubeflow, Argo Workflows, MLflow, ZenML, and/or Vertex AI Pipelines.
- Strong Python and Bash skills.
- Experience building CI/CD pipelines for ML and/or GenAI applications.
- Practical experience with Generative AI and LLM applications.
- Experience with LangGraph or similar AI orchestration frameworks.
- Knowledge of LLM evaluation, RAG evaluation, model monitoring, and drift detection.
- Familiarity with Kafka, Spark, SQL/NoSQL databases, and Data Lakes.
- Strong communication, problem-solving, and mentoring skills.
- Spanish: B2 minimum, C1 preferred.
- English: B2 minimum.