Senior MLOps Engineer – Remote Production AI & LLMs

Dynatron; United States; A distancia; USD 150.000 - 230.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote environment

Professional development

Ownership of production systems

Work with U.S. teams

Descripción de la vacante

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.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

ML Ops

Production ML

LLM workloads

Python

Cloud AWS

Observability

Communication

Educación

Bachelor’s degree in Computer Science or Engineering

Herramientas

AWS

Docker

Kubernetes

Descripción del empleo

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.