ML Ops Senior Engineers

Overview

Contract - W2
Contract - 12

Skills

Python
PyTorch
TensorFlow
Scikit-learn
ML frameworks

Job Details

Technical Skills

Must have:

Expertise in Python and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).

Strong Experience in deployment/devops technologies: CI/CD pipelines, Kubernetes/Docker, and infrastructure-as-code tools (Terraform, Ansible, etc.). and cloud-native architectures (Google Cloud Platform and Aruze), monitoring and observability for ML workloads

Advanced understanding of ML pipeline orchestration tools like Kubeflow, MLflow, Airflow, or TFX.

Nice to have:

Experience with distributed computing frameworks (e.g., Spark, Ray, Dask) is a plus.

Familiarity with model explainability, fairness, and bias detection tools is highly desirable.

Strong knowledge of security best practices for ML systems, including data encryption, API security, and governance.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.