ML Ops Infrastructure Engineer

Deepgram
United States
Workplace: RemoteFull timeUSD 160,000 - 220,000 annuallyFunction: DevOps, Cloud & InfrastructureExperience: 4+ yearsSkills: ["Problem-solving","Collaboration"]

Bridge research and production for ML models by building and maintaining CI/CD pipelines, deployment and testing infrastructure, A/B testing, monitoring, and automated retraining to deliver models from experimentation to production at scale.

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FursaFursa
Deepgram
Deepgram
5 months ago

ML Ops Infrastructure Engineer

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 12 hours agoStatus: Live

Job Summary

Bridge research and production for ML models by building and maintaining CI/CD pipelines, deployment and testing infrastructure, A/B testing, monitoring, and automated retraining to deliver models from experimentation to production at scale.
Location: United States
Workplace: Remote
Employment Type: Full time
Job Function: DevOps, Cloud & Infrastructure
Seniority: Mid level

Key Responsibilities

  • •Design and build CI/CD pipelines specifically tailored for ML model development, validation, and deployment
  • •Architect and maintain model deployment pipelines that move models from research environments through staging to production with confidence
  • •Build A/B testing infrastructure that enables controlled rollouts of new models and measures real-world performance impact
  • •Implement comprehensive monitoring for model performance in production -- accuracy metrics, latency, drift detection, and regression alerts
  • •Develop automated retraining pipelines that trigger on data changes, performance degradation, or scheduled cadences

Pay and Benefits

Salary: USD 160,000 - 220,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionWellness Stipend401kPaid LeaveParental LeaveHome Office

Key Requirements

  • •4+ years of experience in MLOps, DevOps, or infrastructure engineering with a focus on ML systems
  • •Strong proficiency in Python and experience building automation and tooling for ML workflows
  • •Deep experience with CI/CD systems and building pipelines for software and model delivery
  • •Hands-on experience with Docker and Kubernetes for containerized workload management
  • •Practical experience deploying and serving ML models in production environments
Experience:4+ yearsAI/MLCloud
Skills:Problem-solvingCollaboration
Tech Stack:PythonDockerKubernetesCI/CDTriton Inference ServerTensorRTONNX RuntimeTerraformPulumiPrometheusGrafanaDatadog

Company Brief

Deepgram
Deepgram builds a real-time Voice AI platform delivering speech-to-text, text-to-speech, and voice-agent APIs for developers and enterprises, focusing on low-latency, high-accuracy voice models and scalable deployment options.
Industry: API Platforms
Company Size: Medium (51 to 250 employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series C
Headquarters: San Francisco, United States
Founded: 2015
Glassdoor
Glassdoor: 4.5
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