Vibe

πŸ‘₯ 101-250πŸ’° $22,500,000 Series A about 1 year agoInternetAdvertisingTVMarketingπŸ’Ό Private Company
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Vibe is revolutionizing TV advertising for small and medium-sized businesses. Our self-serve platform empowers advertisers to launch and manage campaigns across streaming TV and OTT channels, offering unparalleled performance and insights. We are building the "Google Ads of Streaming", making TV advertising as simple and fast as social ads. We are at the forefront of the adtech industry, providing a cutting-edge platform that allows businesses to target specific audiences, optimize spending, and measure results in real-time. Our tech stack includes technologies like AWS, Terraform, Kubernetes, Python, and Prometheus, reflecting our commitment to scalable and reliable systems. We foster a DevOps-oriented engineering culture, emphasizing automation, developer experience, and data-driven decision-making. We’re also committed to cybersecurity best practices. Founded in 2021 by experienced adtech entrepreneurs, Vibe has quickly gained momentum, onboarding over 2,000 clients and generating $47M in revenue in 2024. We've secured $25M in Series A funding, fueling our ambitious growth plans. We are a remote-first company with a global presence, offering competitive compensation and a range of benefits, including excellent health insurance and perks like childcare placement assistance.

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πŸ“ France

🧭 Full-Time

πŸ” Streaming Advertising

  • 8+ years of experience in relevant technical roles (Software Engineering, Data Engineering, ML Ops, or Infrastructure), with a strong foundation to build and scale ML infrastructure
  • Strong coding skills in Python, CI/CD, and Infrastructure as Code (Terraform, Ansible)
  • Deep expertise in ML Infrastructure: training orchestration (Dagster, Airflow), feature stores, live model monitoring, and distributed/multi-GPU training (TensorFlow, PyTorch)
  • Extensive cloud & scalability experience: deploying ML models on AWS/GCP, optimizing real-time inference, handling large-scale data pipelines, and implementing cost-efficient FinOps strategies
  • Build and optimize automated ML training pipelines (MLflow, Dagster)
  • Improve scalability and performance (multi-GPU, caching, distributed architectures)
  • Deploy and optimize real-time inference systems to ensure sub-20ms latency at scale
  • Implement monitoring and observability for models (Prometheus, Grafana, Evidently AI)
  • Optimize cloud costs and resource management (AWS Spot Instances, auto-scaling Kubernetes, FinOps)

AWSPythonGCPKubernetesMLFlowPyTorchData engineeringGrafanaPrometheusTensorflowCI/CDTerraformAnsibleSoftware Engineering

Posted 8 days ago
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πŸ“ France

🧭 Full-Time

  • Proven experience in designing, implementing, and maintaining highly available and fault-tolerant systems
  • Deep knowledge of AWS with Terraform, Kubernetes, and CI/CD pipeline management (GCP experience is a plus)
  • Strong understanding of security principles, IAM, RBAC, and network security
  • Proficiency in Python (Go or Rust as a plus)
  • Experience with Prometheus/Grafana (OpenTelemetry as a plus)
  • Ensure high availability (99.99%) and prevent service disruption
  • Automate deployment & infrastructure management (Terraform, Kubernetes, CI/CD)
  • Monitor system health & performance (Prometheus, Grafana, OpenTelemetry)
  • Optimize cloud costs & FinOps strategies (AWS, GCP, Spot Instances)
  • Implement security best practices and compliance policies

AWSPythonCloud ComputingCybersecurityKubernetesGrafanaPrometheusCI/CDRESTful APIsLinuxDevOpsTerraformMicroservices

Posted 9 days ago
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