Senior MLOps Engineer (GCP)

Location: Remote Lithuania

Company

hirify.global develops cybersecurity solutions that help customers monitor, manage, and protect risks associated with digital identities and personal information.

What you will do

• Architect and manage scalable machine learning infrastructure on Google Cloud using Vertex AI, GKE, GCS, Cloud Run, and GPU/TPU compute.
• Own the full model deployment lifecycle and build high-throughput, low-latency inference services with Docker and serving tools such as Triton Inference Server, vLLM, and MLflow.
• Build reproducible pipelines for model training, testing, evaluation, and deployment using Airflow, Vertex AI Pipelines, GitHub Actions, and ArgoCD.
• Implement system and machine learning observability, including latency, throughput, uptime, feature drift, prediction accuracy, and data distribution monitoring.
• Provide scalable training environments and standardized deployment templates for AI and research engineers.
• Turn AI prototypes and notebooks into secure, resilient, auto-scaling microservices while supporting feature stores, dataset versioning, and stream or batch processing.

Requirements

• At least 5 years of hands-on experience designing, deploying, and maintaining production machine learning workloads in cloud environments.
• Deep practical experience with GCP, including Vertex AI, Cloud Storage, GKE, Cloud Run, IAM, and VPC configurations.
• Expertise with containerization, Kubernetes/GKE, and specialized model serving tools such as Triton, vLLM, and MLflow.
• Experience with Airflow, Vertex AI Pipelines, modern CI/CD, and Terraform for infrastructure as code.
• Proficiency in Python and SQL for scripting, automation, API development, and data manipulation.
• Hands-on experience with logging, telemetry, and drift detection using Grafana, Prometheus, GCP Cloud Monitoring, or comparable ML observability frameworks.

Nice to have

• Experience running large-scale LLM or deep learning inference and training workloads.
• GCP Professional Machine Learning Engineer or Professional Cloud Architect certification.
• Familiarity with feature stores such as Feast or Vertex AI Feature Store.

Culture & Benefits

• Work on cybersecurity products addressing real customer protection needs.
• Contribute directly to a nimble organization where individual impact is visible.
• Work with cross-functional AI research, data engineering, backend, and software engineering teams.
• Develop new technologies, products, and markets in a fast-paced, growth-oriented environment.
• Inclusive workplace committed to preventing discrimination and harassment.