Top 199 Machine learning engineer Jobs in Phoenix, Az

AI Engineer
Better Direct —Tempe, AZ
- $60,000 - $80,000 a year
- Full-time
- Background check
- Azure
- System design
Quick Apply
Sequence Integrator
ASML —Phoenix, AZ
- Full-time
- Customer service
- Bachelor of Science
- Writing skills
Sr Databricks Data Engineer
Deloitte —Tempe, AZ
- $137,500 - $193,600 a year
- Full-time
- Azure
- Management
- Computer Science
Packaging Module Development Engineer
Intel —Phoenix, AZ
- $115,110 - $219,550 a year
- Full-time
- Management
- Customer service
- Engineering
- Health insurance
Dev Ops System Administrator
WSG —Scottsdale, AZ
- Full-time
- Computer science
- 6 years
- Computer Science
- Relocation assistance
- Health insurance
Quick Apply
11d
Data Scientist - AI Trainer
DataAnnotation —Mesa, AZ
- $50 - $100 an hour
- Contract
- Remote
- English
- Mid-level
- Bachelor's degree
- Flexible schedule
Packaging Module Development Engineer
Intel —Phoenix, AZ
- $115,110 - $219,550 a year
- Full-time
- Management
- Customer service
- Mid-level
- Health insurance
Databricks Data Engineer
Deloitte —Tempe, AZ
- $86,700 - $170,900 a year
- Full-time
- Azure
- Computer Science
- Up to 50% travel
14d
Director, Space Ground Systems
General Dynamics Mission Systems, Inc —Scottsdale, AZ
- $239,881 - $259,559 a year
- Urgently hiring
- 18 years or older
- Engineering
- Master's degree
2d
AI and Data Science Engineer III
Deloitte —Tempe, AZ
- $113,100 - $208,300 a year
- Full-time
- Azure
- Oracle
- Doctoral degree
Dev Ops System Administrator
General Dynamics Mission Systems, Inc —Scottsdale, AZ
- $126,862 - $137,269 a year
- Full-time
- Computer science
- 6 years
- Computer Science
Senior Digital Signal Processing Systems Engineer
General Dynamics Mission Systems, Inc —Scottsdale, AZ
- $157,487 - $167,000 a year
- Full-time
- Hybrid work
- 6 years
- Master's degree
- Analysis skills
- Paid parental leave
- Health insurance
Solution Architect
LA MESA RV INC —Phoenix, AZ
- Full-time
- Azure
- Computer Science
- 8 years
- Health insurance
- 401(k)
Quick Apply
AI Engineer
KUBRA —Tempe, AZ
- Full-time
- Hybrid work
- Writing skills
- System design
- SQL
- Health savings account
- Health insurance
Quick Apply
Mechanical Engineer - Phoenix, AZ
The Lane Construction Corporation —Phoenix, AZ
- Extended hours
- Microsoft Excel
- Bachelor of Science
- ERP systems
11d
AI/ML Engineer
Diligent Tec Inc —Scottsdale, AZ
- $130,000 - $140,000 a year
- Full-time
- Azure
- 8 years
- AWS
Quick Apply
AI/ML Engineer - Computer Vision
Prime Solutions Group, Inc. —Goodyear, AZ
- $110,000 - $180,000 a year
- Full-time
- Azure
- Computer Science
- AWS
Quick Apply
9d
Systems Engineer
Nlets - The International Justice and Public Safety Network —Phoenix, AZ
- $80,300 - $110,000 a year
- Full-time
- Hybrid work
- 6 years
- Computer Science
- System design
- Health savings account
- Paid holidays
Quick Apply
GCP Lead Engineer
Technologent —Phoenix, AZ
- Contract
- DevOps
- 8 years
- Analysis skills
Quick Apply
8d
Low Code AI Engineer
NOVA DINE LLC —Scottsdale, AZ
- Full-time
- Remote
- Computer science
- Azure
- Computer Science
- Disability insurance
- Health insurance
Quick Apply

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machine learning engineer jobs near phoenix, az

AI Engineer

Better Direct -
Tempe, AZ

Quick Apply

Job Details

Full-time
$60,000 - $80,000 a year

Qualifications

AI models
Index optimization
TensorFlow
Data transformation pipeline development
NumPy
Generative models
AI platforms (beyond public GPTs)
Computational framework
Pandas
Machine intelligence
GitHub
Neural networks
Metadata
Benchmarking
Machine learning libraries
Model evaluation
Machine learning frameworks

Full Job Description

About the Role

We are looking for a motivated AI Engineer who is passionate about large language models (LLMs), machine learning, and applied AI systems. This position is focused on building real-world AI systems, not just experimenting with models.

You will work on projects involving open-source LLMs, retrieval-augmented generation (RAG) pipelines, vector databases, and AI-powered document processing systems. The goal is to build scalable AI workflows that solve practical problems such as knowledge retrieval, document analysis, and AI-assisted automation.

This role is ideal for engineers who want hands-on experience deploying AI systems used in production-like environments.

Responsibilities

AI & Machine Learning Development

Build and experiment with open-source LLM and SLM pipelines.
Design and implement Retrieval Augmented Generation (RAG) systems.
Develop AI pipelines capable of processing documents, PDFs, and structured data.
Work with embedding models and vector search systems.
Implement prompt engineering, model evaluation, and response optimization.
Assist with fine-tuning or adapting open-source models when necessary.

Data Processing & AI Pipelines

Build ingestion pipelines for PDFs, documents, and datasets.
Implement document chunking, embedding generation, and indexing strategies.
Work with vector databases to support semantic search and retrieval.
Optimize pipelines for latency, scalability, and cost efficiency.

Research & Experimentation

Evaluate different open-source models and architectures.
Compare embedding models and retrieval methods.
Test improvements in RAG performance and hallucination reduction.
Explore emerging techniques in Vision Language Models (VLMs).

Collaboration

Work with engineers to integrate AI components into applications.
Document experiments and technical findings.
Participate in weekly discussions on AI architecture decisions and improvements.

Required Skills & Knowledge

Core AI Knowledge

Strong understanding of:
Machine Learning
Neural Networks
Deep Learning fundamentals
Familiarity with:
Large Language Models (LLMs)
Small Language Models (SLMs)

Programming

Strong proficiency in Python
Experience with AI/ML frameworks such as:
PyTorch
TensorFlow
Hugging Face Transformers

AI Application Frameworks

Experience with:

LangChain or similar orchestration frameworks
Prompt engineering and AI workflow building

Vector Databases

Conceptual and practical understanding of any vector databases such as:

Pinecone
ChromaDB
Milvus
Qdrant
FAISS
Weaviate

Understanding of:

embeddings
similarity search
indexing strategies
metadata filtering

RAG Systems

Ability to design or understand:

Retrieval pipelines
Document chunking strategies
Embedding pipelines
Hybrid search
Context window optimization
RAG evaluation methods

Data Processing

Experience with:

PDF extraction
Document parsing pipelines
Data preprocessing

Bonus Knowledge

Vision Language Models (VLMs)
Multimodal AI systems
Distributed AI inference
GPU inference optimization

Preferred Project Experience

Candidates should have completed at least 1–3 hands-on AI projects, such as:

Example Project 1 – RAG Knowledge Assistant

Built a chatbot that answers questions from internal documentation.
Implemented document ingestion, chunking, embedding generation, and vector search.
Used LangChain + vector database + open-source LLM.

Example Project 2 – Document AI System

Created a system that extracts structured information from PDFs.
Built pipelines for PDF parsing → embeddings → AI summarization.

Example Project 3 – AI Research Experiment

Compared multiple embedding models and evaluated search accuracy.
Benchmarked RAG response quality and hallucination rates.

Example Project 4 – LLM Application

Built a real-world tool using open-source models (e.g., summarizer, Q&A system, coding assistant).

Real-World Experience

Candidates may also have experience such as:

Contributing to open-source AI projects
Participating in AI hackathons
Research experience in machine learning or NLP
Building production-style AI APIs
Deploying models using Docker or cloud platforms
Working with LLM inference servers (vLLM, TGI, Ollama, etc.)

Tools & Technologies (Exposure Preferred)

AI / ML

PyTorch
Hugging Face
Transformers
Sentence Transformers

LLM Tools

LangChain
LlamaIndex
Open-source LLMs (LLaMA, Mistral, etc.)

Vector Databases

Pinecone
ChromaDB
Milvus
Qdrant
FAISS
Weaviate

Data Tools

Pandas
NumPy

Deployment

Docker
REST APIs / FastAPI
Basic cloud exposure (AWS/GCP/Azure)

What You Will Gain

Hands-on experience building real AI systems
Exposure to modern LLM architecture and AI infrastructure
Experience with RAG pipelines and vector databases
Mentorship from engineers working in applied AI
Opportunity to contribute to real production-style AI tools

Candidate Profile

We are looking for someone who:

Is curious and loves experimenting with AI systems
Enjoys solving practical engineering problems
Can quickly learn new frameworks and models
Is comfortable reading research papers and technical documentation
Has strong problem-solving and debugging skills

Application Requirements

Please include:

Resume
GitHub profile (required)
Links to AI/ML projects
Brief description of a RAG or LLM system you have built

Pay: $60,000.00 - $80,000.00 per year

Work Location: In person

Quick Apply

Refine Your Search

machine learning engineer jobs in phoenix, az

AI Engineer

Sequence Integrator

Sr Databricks Data Engineer

Packaging Module Development Engineer

Dev Ops System Administrator

Data Scientist - AI Trainer

Packaging Module Development Engineer

Databricks Data Engineer

Director, Space Ground Systems

AI and Data Science Engineer III

Dev Ops System Administrator

Senior Digital Signal Processing Systems Engineer

Solution Architect

AI Engineer

Mechanical Engineer - Phoenix, AZ

AI/ML Engineer

AI/ML Engineer - Computer Vision

Systems Engineer

GCP Lead Engineer

Low Code AI Engineer

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