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# AI Engineer

- **Company:** Centific Global Solutions
- **Location:** Palo Alto, CA, United States (Remote available)
- **Salary:** $165,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Clean Code Principles, Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, C++ (Programming Language), Distributed Computing Environment, Django Web Framework, Python (Programming Language), Machine Learning, Language Modeling, Natural Language Processing, Tensorflow, Software Engineering, Systems Integration, Web Application Frameworks, Reinforcement Learning, Google Cloud, Pytorch, LangChain, Flask (Web Framework), Large Language Models, Deep Learning, Agentic-AI, Fastapi, Build Management, Kubernetes, Information Technology, Production Code, Transformer Architectures, AutoGen, Software Coding, Restful APIs, Docker
- **Published:** October 11, 2026
- **Apply:** https://startup.jobs/ai-engineer-centific-global-solutions-sl-10357411

## About the Role

* Bachelor's degree in Computer Science, Engineering, or a related field (Master's preferred).
 * Proven experience in developing NLP models, with a solid understanding of language modeling and transformer architectures.
 * Proficiency in programming languages, particularly Python, Java or C++, with strong coding practices.
 * Experience with machine learning frameworks such as PyTorch or TensorFlow for building and optimizing NLP models.
 * Familiarity with web frameworks, particularly fast API, Flask, Django or similar, for creating APIs to serve models.
 * Understanding of Agentic AI frameworks like LangChain, LangGraph, AutoGen, or Crew AI.
 * Strong analytical and problem-solving skills, with the ability to work effectively both independently and in a team environment.
 * Excellent communication skills to convey technical concepts to diverse audiences.

What would help you stand out:

 * PhD in Computer Science or equivalent combination of education, training, and experience
 * Industry experience in Artificial Intelligence projects
 * Track record of publishing scientific papers in top conferences and journals
 * Strong communication skills (written and verbal), motivation for international collaboration
 * Experience with ML optimization including distributed training, low-rank adaptation
 * Experience with cloud platforms (AWS, Azure, GCP)
 * Knowledge of containerization using Docker and orchestration with Kubernetes.
 * Familiarity with other domains such as deep learning, computer vision or reinforcement learning.

## Description

We are looking for a passionate and skilled AI Engineer to join our innovative team. The ideal candidate will have a deep understanding of natural language processing with specific knowledge of language models and transformer architecture. Proficiency in coding with PyTorch or TensorFlow is essential, as well as experience in developing production-ready applications using fast API or similar frameworks. Familiarity with tools like LangChain, LangGraph, or Agentic AI is a plus, as well as experience with Docker and Kubernetes for deployment. This is a fantastic opportunity to work on cutting-edge NLP / LLM projects that solve the hard problems and advance the field., * Develop, fine-tune, and deploy state-of-the-art NLP models using transformer architectures for various applications.

 * Implement robust and production-quality code, utilizing frameworks such as PyTorch or TensorFlow.
 * Design and build RESTful APIs with either FastAPI, Flask, Django or similar technologies to support model integration and application development.
 * Collaborate with product managers, data scientists, and other stakeholders to gather requirements and deliver effective NLP solutions.
 * Optimize model performance and scalability in production settings while ensuring reliability and efficiency.
 * Monitor, troubleshoot, and enhance existing NLP models deployed in production environments.
 * Stay current on advancements in NLP and machine learning, applying best practices to ongoing projects.