5 natural language processing engineer jobs at 3 companies in United States
🚀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.
Software Engineer in Natural Language Processing (NLP) and Machine Learning (ML)
Seattle, Washington, United States
OnsiteFull Time
AppleNASDAQ: AAPL: Designs and sells consumer electronics, software, and online services.
Experience in natural language processing, machine learning, and generative AI; software engineering skills to research, develop, and deploy ML/NLP technologies for on-device and cloud; strong collaboration and communication.
Software Engineer in Natural Language Processing (NLP) and Machine Learning (ML)
Cupertino, California, United States
OnsiteFull Time
AppleNASDAQ: AAPL: Designs and sells consumer electronics, software, and online services.
Experience in natural language processing and machine learning, building and deploying ML/NLP systems for on-device and private cloud, strong collaboration and communication skills.
AppleNASDAQ: AAPL: Designs and sells consumer electronics, software, and online services.
Experience building machine learning, natural language processing, and search systems at scale in high-performance computing environments with large datasets and high query volumes.
Writer: Platform for building and deploying enterprise generative AI agents.
5+ YOE5+ years of experience building and deploying ML/AI systems; proficient in Python and frameworks (PyTorch, TensorFlow, or JAX); strong ML/natural language processing background; experience with cloud (AWS, GCP, Azure) and MLOps; able to deliver scalable software; strong collaboration and problem-solving.
ServiceNowNYSE: NOW: Provides a cloud platform for automating enterprise digital workflows.
Experience in information retrieval or ML ranking, query-log analysis, text processing, natural language understanding, and building ranking features and evaluation metrics.