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Sequen AI logo

Staff, MLOps Engineer

Sequen AIPersonalization & company
New York, United States$220,000 – $280,000Lead
White Star Capital
Threshold Ventures
Greycroft logo
Greycroft
Correlation Ventures
Vinyl Capital
Data & AI

About the role

TL;DR

Build, scale, and operate critical systems for AI models in production.

  • We are looking for an MLOps Engineer to build, scale, and operate the critical systems that power Sequen’s AI models in production.
  • This is a foundational, purely infrastructure-focused role sitting at the intersection of machine learning, backend distributed systems, and platform performance.
  • Key Responsibilities Build ML infrastructure: Design, operate, and maintain robust systems for low-latency model deployment, distributed inference pipelines, and automated real-time telemetry.
  • Scale ranking systems: Move models cleanly from experimentation to production, optimizing trade-offs between latency, throughput, and cost.
  • Implement model CI/CD: Build reliable infrastructure for automated model versioning, canary releases, and zero-downtime rollbacks.
  • Drive system observability: Architect and monitor real-time pipelines to track model performance and system reliability.
  • Develop evaluation loops: Engineer robust evaluation pipelines to continuously validate live inference accuracy.
  • Requirements 4–8+ years of practical experience in MLOps, Machine Learning Engineering, or distributed platform/infrastructure engineering.
  • Hands-on experience deploying and serving ultra-low-latency machine learning models under heavy, real-time concurrent workloads.
  • Deep, production-grade proficiency with Python and PyTorch.
  • Comfortable across major cloud platforms (AWS, GCP, or Azure) utilizing modern containerization and orchestration tooling (Docker, Kubernetes).
  • Experience designing robust, scalable data pipelines, model registries, and automated CI/CD infrastructures.
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Required skills

PythonPyTorchDockerKubernetesAWSGoogle CloudAzureMLflowCI/CDMicroservicesREST API

Nice-to-have skills

RustLLMs

Domain expertise

airetail

Benefits & perks

Performance Bonus, Meaningful Equity, Full premium medical/dental/vision coverage, Unlimited paid time off

Tech stack

PythonPyTorchDockerKubernetesAWSGoogle CloudAzureMLflowRust

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