Point Wild

Point Wild

Point Wild specializes in providing comprehensive online security solutions, including consumer VPN and antivirus services, while also supporting businesses with tools to enhance customer retention and address data breaches.

Internet Software & Services

Description

  • Architect and manage GCP machine-learning infrastructure using Vertex AI, GKE, GCS, Cloud Run, and GPU/TPU compute.
  • Own the end-to-end deployment and serving lifecycle for production ML models.
  • Build high-throughput, low-latency inference services with containers and tools such as Triton, vLLM, and MLflow.
  • Develop automated, reproducible pipelines for model training, testing, evaluation, and deployment.
  • Implement system and ML observability, including latency, throughput, uptime, drift, accuracy, and data-shift monitoring.
  • Provide scalable training environments, runtime infrastructure, and standardized deployment templates for AI engineers.
  • Integrate ML pipelines with feature stores, dataset versioning, and stream- and batch-processing workflows.
  • Lead the transition of AI prototypes and notebooks into secure, resilient, auto-scaling microservices.
  • Collaborate with AI researchers, data engineers, and backend teams to support production reliability.

Requirements

  • At least 5 years of hands-on experience designing, deploying, and maintaining production ML workloads in cloud environments.
  • Deep practical experience with GCP, including Vertex AI, Cloud Storage, GKE, Cloud Run, IAM, and VPC configurations.
  • Expertise with Docker, Kubernetes/GKE, and model-serving tools such as Triton, vLLM, and MLflow.
  • Experience with Airflow, Vertex AI Pipelines, GitHub Actions, and ArgoCD.
  • Solid experience managing cloud infrastructure with Terraform.
  • Proficiency in Python and SQL for automation, API development, scripting, and data manipulation.
  • Hands-on experience with logging, telemetry, and ML observability tools such as Grafana, Prometheus, and GCP Cloud Monitoring.
  • Experience with large-scale LLM or deep-learning inference and training workloads (preferred).
  • GCP Professional Machine Learning Engineer or Cloud Architect certification (preferred).
  • Familiarity with feature stores such as Feast or Vertex AI Feature Store (preferred).

Benefits

  • Opportunity to solve real customer cybersecurity problems and see the direct impact of your work.
  • Career growth through exposure to new technologies, products, and markets in a fast-paced environment.
  • Collaborative workplace with talented colleagues and opportunities to make meaningful contributions.
  • Inclusive workplace committed to equal opportunity and free from discrimination and harassment.

Interested in this position?

Apply directly on the company website

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