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# AI Engineer

- **Company:** The Standard
- **Location:** New York, NY, United States
- **Salary:** $160,000.0 - $230,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Configuration Management Databases, Information Retrieval, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, AI Infrastructure, Enterprise Software Applications, Pytorch, Large Language Models, Information Technology, Machine Learning Operations, Natural Language Understanding
- **Published:** July 12, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=1d1f2162b837d3c0

## About the Role

* Bachelor's or Master's in Computer Science, AI/ML, or related field; PhD is a plus.
 * Strong software engineering fundamentals (Python preferred) and experience with ML frameworks such as PyTorch or TensorFlow.
 * Experience with one or more of: natural language processing (NLP), large language models (LLMs), information retrieval, graph ML, or time-series forecasting.
 * Understanding of modern MLOps practices: model versioning, deployment, monitoring, and lifecycle management.
 * Comfort working in a fast-paced startup environment with end-to-end ownership.
 * Bonus: experience applying AI in enterprise software or ITSM contexts.

## Description

Our team is currently seeking AI Engineers that will design, build, and deploy machine learning systems that form the intelligence layer of our ITSM platform. You will work on problems such as natural language understanding of IT tickets, dynamic knowledge extraction, intelligent workflow automation, and predictive insights from complex IT infrastructure data. This is a hands-on engineering role with the opportunity to define the AI foundation of a company from day one., * Research, prototype, and productionize machine learning models for ITSM use cases (ticket triage, incident prediction, workflow recommendations, CMDB inference).

 * Build scalable training and inference pipelines that integrate seamlessly into the core platform.
 * Experiment with LLMs, embeddings, and retrieval-augmented generation (RAG) for IT knowledge and workflow automation.
 * Partner with engineers and product managers to define AI-first features that differentiate our platform.
 * Evaluate performance, optimize models, and ensure reliability, scalability, and cost-efficiency of AI systems.
 * Stay current with advances in machine learning, LLMs, and AI infrastructure, and apply them pragmatically.


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