Machine Learning Engineer/AI Engineer

eTeam; Minneapolis (MN); Remote; Full time

Job summary

A leading company is seeking a Machine Learning Engineer/AI Engineer for a fully remote position. The role focuses on monitoring AI models using Fiddler and Lumenova tools, requiring strong skills in data analysis, bias detection, and model performance metrics. Ideal candidates will have experience in Azure and AI use case implementation. This is a contract position lasting 7 months with potential for extension.

Qualifications

• 3-5 years experience with Fiddler and Lumenova tools.
• Understanding AI model metrics and data analysis.

Responsibilities

• Monitor AI models using Fiddler AI or Lumenova tools.
• Analyze data distributions for biases and detect model drift.

Skills

Data Analysis

Bias Detection

Prompt Engineering

Visualization Skills

Model Explainability

Tools

Fiddler

Lumenova

Azure

Job description

2 days ago Be among the first 25 applicants

This range is provided by eTeam. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$68.75/hr - $80.88/hr

Job Title: Machine Learning Engineer/AI Engineer

Location: Fully Remote

Preferences: Candidates local to Atlanta and Minneapolis are strongly preferred.

Working hours: 8am - 5pm CST

Duration: 7 months on contract with possible extension

Top Requirements

• Fiddler tool (3-5 years)
• Lumenova tool (3-5 years)
• Azure/cloud knowledge (3-5 years)
• AI use case implementation (3-5 years)

Job Description

To effectively monitor AI models using Fiddler AI or Lumenova tools, key skills include:

• Understanding AI model metrics, data analysis, statistical knowledge, familiarity with bias detection techniques, prompt engineering, LLM monitoring capabilities, visualization skills, and interpreting model explanations to identify issues like hallucinations, safety violations, and data drift.

Specific skills to focus on when monitoring Fiddler AI and Lumenova AI tools:

• Model performance metrics: Accuracy, precision, recall, F1-score, perplexity, BLEU score (depending on the AI task); monitoring changes over time to detect model drift.
• Data analysis: Identifying patterns and anomalies, analyzing data distributions for biases.
• Bias detection: Understanding protected attributes, assessing bias across demographics, utilizing fairness metrics like disparate impact and equal opportunity.
• Prompt engineering: Crafting prompts to test model behavior and identify issues; understanding prompt influence.
• LLM-specific monitoring: Detecting hallucinations, safety violations, prompt injection attacks.
• Visualization skills: Creating dashboards, using tools like 3D UMAP for data clustering.
• Model explainability: Interpreting explanations to improve models.
• Platform knowledge: Familiarity with Fiddler's or Lumenova's features like data ingestion, monitoring, bias detection, root cause analysis.
• Azure/cloud knowledge: Maintaining and debugging cloud platform stacks, collaborating with engineers and vendors.

Seniority Level

• Mid-Senior level

Employment Type

• Contract

Job Function

• Information Technology

Industries

• Financial Services, Information Services, IT Services, and IT Consulting