Senior ML Engineer

Data Essentia; United States; Remote; USD 130,000 - 170,000; Full time

Job summary

Data Essentia is seeking a machine learning engineer to build and run ML systems for business customers, taking models from early investigation through production deployment. The work spans the full lifecycle, including developing models and making them reliable in live environments.

You will apply Python and an ML framework to implement solutions, own end-to-end ML processes, and apply MLOps practices to support deployment and operations in production.

Qualifications

• ≥5 years of machine learning engineering experience.
• Strong Python skills.
• Experience with PyTorch, TensorFlow, or JAX.
• Experience with MLflow, Kubeflow, or SageMaker.

Responsibilities

• Develop and deploy machine learning systems for production use.
• Own work across the ML lifecycle, from research to serving.
• Apply Python and an ML framework to implement solutions.
• Use MLOps practices and tools to support model deployment and operations.

Skills

Python

ML lifecycle

Production ML

Tools

PyTorch

TensorFlow

JAX

MLflow

Kubeflow

SageMaker

Job description

Role overview

Build and run machine learning systems for business customers, taking models from early investigation through production deployment. The work spans the full lifecycle, including developing models and making them reliable in live environments.

Responsibilities

• Develop and deploy machine learning systems for production use.
• Own work across the ML lifecycle, from research to serving.
• Apply Python and an ML framework to implement solutions.
• Use MLOps practices and tools to support model deployment and operations.

Requirements

• At least five years of machine learning engineering experience.
• Strong Python skills.
• Experience with at least one of PyTorch, TensorFlow, or JAX.
• Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker.

Nice to have

• Experience putting large language models into production.

Benefits and work setup

• Full-time role, remote within the United States.