

ValueBase Consulting
Senior/Lead AI/ML Engineer in Phoenix, AZ
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior/Lead AI/ML Engineer in Phoenix, AZ, offering a 6+ month W2 contract at $60/hr. Requires 6–8 years of experience in AI/ML, strong skills in time series forecasting, anomaly detection, and LLM integration.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
480
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🗓️ - Date
November 17, 2025
🕒 - Duration
More than 6 months
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Phoenix, AZ
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🧠 - Skills detailed
#PyTorch #Java #React #Python #MongoDB #Programming #Observability #GCP (Google Cloud Platform) #ML (Machine Learning) #TensorFlow #Grafana #Cloud #R #Forecasting #Azure #Anomaly Detection #Angular #AI (Artificial Intelligence) #Agile #Classification #Scala #jQuery #Version Control #Databases #PostgreSQL #Deep Learning #GIT #Time Series #MySQL
Role description
AI/ML Engineer (W2 Contract – $60/hr) Location: Phoenix, AZ (Onsite
• 5 Days/Week
• Local Candidates Only) Job Type: 6+ Month Contract-to-Hire (W2) Interview: Inperson Interview Required
About the Role We are seeking an experienced AI/ML Engineer for an onsite role in Phoenix, AZ. This is a W2 contract position at $60/hr, with the potential to convert to full-time after 6 months. Local candidates only, as this role requires 5 days per week onsite.
You will design and develop ML and deep learning solutions for observability data (AIOps), build intelligent forecasting and anomaly detection models, and integrate modern LLM-based capabilities including prompt engineering, fine-tuning, and RAG pipelines.
Responsibilities
Design and develop ML/DL algorithms for observability data (AIOps)
Build solutions for time series forecasting, anomaly detection, and event classification
Integrate LLMs using prompt engineering, fine-tuning, and Retrieval-Augmented Generation (RAG)
Work with MCP client/server development for Grafana or similar tooling
Collaborate with cross-functional teams to deliver scalable AI-driven features
Required Skills
6–8 years of hands-on AI/ML engineering experience
Strong background in:
Time series forecasting
Anomaly detection
Event classification
Experience with LLMs (prompt engineering, fine-tuning, RAG)
Proficiency with MCP-based integrations (Grafana or similar)
Programming: Python, R
ML Frameworks: TensorFlow or PyTorch, scikit-learn
Cloud: Google Cloud (GCP) and/or Azure
Front-End: React, Angular, Vue.js, or jQuery
Design Tools: Figma, Adobe XD, or Sketch
Databases: MySQL, MongoDB, or PostgreSQL
Server-Side: Python, Node.js, or Java
Version Control: Git
Understanding of testing frameworks and Agile methodologies
Excellent communication and collaboration skills
AI/ML Engineer (W2 Contract – $60/hr) Location: Phoenix, AZ (Onsite
• 5 Days/Week
• Local Candidates Only) Job Type: 6+ Month Contract-to-Hire (W2) Interview: Inperson Interview Required
About the Role We are seeking an experienced AI/ML Engineer for an onsite role in Phoenix, AZ. This is a W2 contract position at $60/hr, with the potential to convert to full-time after 6 months. Local candidates only, as this role requires 5 days per week onsite.
You will design and develop ML and deep learning solutions for observability data (AIOps), build intelligent forecasting and anomaly detection models, and integrate modern LLM-based capabilities including prompt engineering, fine-tuning, and RAG pipelines.
Responsibilities
Design and develop ML/DL algorithms for observability data (AIOps)
Build solutions for time series forecasting, anomaly detection, and event classification
Integrate LLMs using prompt engineering, fine-tuning, and Retrieval-Augmented Generation (RAG)
Work with MCP client/server development for Grafana or similar tooling
Collaborate with cross-functional teams to deliver scalable AI-driven features
Required Skills
6–8 years of hands-on AI/ML engineering experience
Strong background in:
Time series forecasting
Anomaly detection
Event classification
Experience with LLMs (prompt engineering, fine-tuning, RAG)
Proficiency with MCP-based integrations (Grafana or similar)
Programming: Python, R
ML Frameworks: TensorFlow or PyTorch, scikit-learn
Cloud: Google Cloud (GCP) and/or Azure
Front-End: React, Angular, Vue.js, or jQuery
Design Tools: Figma, Adobe XD, or Sketch
Databases: MySQL, MongoDB, or PostgreSQL
Server-Side: Python, Node.js, or Java
Version Control: Git
Understanding of testing frameworks and Agile methodologies
Excellent communication and collaboration skills






