Senior MLOps Engineer – Remote Production AI & LLMs

Dynatron

United States

Remote

USD 150,000 - 230,000

Full time

6 days ago
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Benefits offered by this job

Remote environment
Professional development
Ownership of production systems
Work with U.S. teams

Job summary

Dynatron is seeking a Senior Machine Learning Engineer (MLOps) to own the production ML infrastructure and lifecycle for its AI workloads. You’ll design pipelines, enforce governance, and ensure reliable deployment from development to production with strong observability and cost controls.

You will support traditional ML and generative AI workloads, partnering with U.S.-based Data Science teams and operating across global time zones. This is a senior, hands-on IC role with significant ownership.

Qualifications

  • 6+ years of software engineering or ML-related experience.
  • 3+ years deploying AI/ML in production.
  • Experience with traditional ML and LLM workloads in production.
  • Strong lifecycle understanding from development to deployment, monitoring, retraining, and retirement.

Responsibilities

  • Design, build, and maintain deployment pipelines for models.
  • Establish model versioning, lineage, and registry.
  • Define production-readiness standards for ML/AI workloads.
  • Partner with Data Scientists to ensure production-ready handoffs.
  • Own production monitoring of model performance, latency, and cost.
  • Operationalize generative AI and retraining infrastructure.

Skills

ML Ops
Production ML
LLM workloads
Python
Cloud AWS
Observability
Communication

Education

Bachelor’s degree in Computer Science or Engineering

Tools

AWS
Docker
Kubernetes

Job description

Dynatron is seeking a Senior Machine Learning Engineer (MLOps) to own the production ML infrastructure and lifecycle for its AI workloads. You’ll design pipelines, enforce governance, and ensure reliable deployment from development to production with strong observability and cost controls.

You will support traditional ML and generative AI workloads, partnering with U.S.-based Data Science teams and operating across global time zones. This is a senior, hands-on IC role with significant ownership.

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