ML Systems Engineer: Production-Ready Model Pipelines

Clear Demand; Scottsdale (AZ); On-site; USD 120,000 - 180,000; Full time

Job summary

Clear Demand in Scottsdale, AZ, seeks a machine learning engineering specialist focused on ML systems, model development, evaluation, and inference workflows. You will help build production-ready pipelines for product matching, similarity search, and explainability.

You’ll work with data scientists and engineers to translate model capabilities into scalable workflows, improve performance, and surface actionable insights through dashboards and reports.

Qualifications

• Experience building ML inference pipelines and production-ready models.
• Ability to analyze model outputs, perform error analysis, and measure metrics.
• Strong SQL and Python skills for data extraction and analysis.
• Familiarity with ML ops, model monitoring, and experimentation workflows.

Responsibilities

• Build and maintain ML inference pipelines and model-serving workflows.
• Perform model evaluation, error analysis, and experimentation.
• Analyze outputs to identify patterns, thresholds, and improvements.
• Collaborate with Data Scientists to productionize models.
• Support training data prep, labeling strategy, and benchmarks.
• Work on embeddings, vector search, classification, and matching.
• Develop analytical scripts, notebooks, dashboards, and reports.
• Enhance explainability by surfacing signals and evidence.
• Assist automation where predictions drive product workflows.
• Debug production ML issues like drift and data issues.
• Contribute reusable ML utilities and evaluation frameworks.

Skills

Programming

ML fundamentals

Embeddings

Vector search

Model validation

Python

PyTorch / TensorFlow

SQL

Tools

scikit-learn

PyTorch

TensorFlow

Hugging Face

sentence-transformers

Job description

Clear Demand in Scottsdale, AZ, seeks a machine learning engineering specialist focused on ML systems, model development, evaluation, and inference workflows. You will help build production-ready pipelines for product matching, similarity search, and explainability.

You’ll work with data scientists and engineers to translate model capabilities into scalable workflows, improve performance, and surface actionable insights through dashboards and reports.