4 software engineer machine learning jobs at 4 companies in Phoenix, AZ
🚀PromotedHiringCafe
Founding Machine Learning / AI Search Engineer
Cupertino, CA, US
$160k-$310k/yrOn-SiteFull Time
HiringCafe: Building a 100× better job search engine to take on Indeed and LinkedIn.
Build the ML and AI search behind HiringCafe — ranking, recommenders, retrieval, and LLM agents that surface jobs people would never find on their own.
HiringCafe: Building a 100× better job search engine to take on Indeed and LinkedIn.
Help us build a 100× better job search engine. We need a full-stack engineer with great taste, sharp fundamentals, and a track record of shipping polished product on React/Next.js plus a real backend (Firebase, Elasticsearch, Redis, Stripe).
IntelNasdaq: INTC: Designs and manufactures microprocessors and semiconductor components.
5+ YOEBS in CS/EE/Math or related STEM, 5+ years software development experience, 2+ years ML engineering or research, proficient in Python and LLM architectures, experience with model training and multi-GPU debugging.
Prime Solutions Group: Provides systems and software engineering for defense and national security.
4+ YOESenior ML Engineer with TS clearance, US citizenship, BS in CS/Engineering/Data Science, 4+ years in ML/AI, Python, ML libraries, Docker, cloud, Agile/CI/CD.
San Francisco or Bengaluru or Chicago or New York City or Phoenix or Singapore or United States or Canada
$170k-$200k/yrOnsiteFull Time
Instawork: Digital marketplace connecting businesses with skilled hourly professionals.
4+ YOE4+ years software engineering experience, Master’s or PhD in AI/ML-related field with 1+ years building ML/CV models for robotics, experience with data pipelines, distributed systems and AWS, strong communication and problem-solving.
AI Engineer/ML Engineer - Senior Developers - AI Training - Mesa, US
Mesa, Arizona, United States
$80/hrRemoteContract, Part Time
Prolific: Platform connecting researchers and AI developers with verified participants.
BS/MS/PhD in CS/AI/Robotics or quantitative field; production ML model experience; deep learning and LLM expertise (prompting, RLHF, RAG); ability to audit models, spot hallucinations, and critique outputs.