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**Intetics** is a global technology company providing custom software application development, distributed professional teams, software product quality assessment, and “all-things-digital” solutions. Based on our proprietary business model of Remote In-Sourcing®, advanced Technical Debt Reduction Platform (TETRA™), and measurable quality management platform (Predictive Software Engineering), Intetics enables clients to achieve measurable business results.
**Position Details**
* Position: AI/ML Engineer
* Seniority: Senior
* Tech Stack: Node.js, Python, TypeScript, AI, ML
* Location: Remote
* Start Date: ASAP
* Duration: Long-term
* Rate: TBD
* English level: Upper-Intermediate
**Role Description**
We are looking for a **Senior AI/ML Engineer** to join our team and work on building and optimizing advanced AI-driven solutions. The ideal candidate has strong engineering expertise, hands-on experience with large language models (LLMs), and a solid background in NLP. You will design, implement, and optimize AI/ML systems, collaborate with cross-functional teams, and contribute to delivering innovative products powered by state-of-the-art AI technologies.
**Requirements**
**Responsibilities:**
* Design, develop, and optimize AI/ML solutions, focusing on LLMs and NLP applications.
* Fine-tune, deploy, and maintain LLMs (OpenAI, Llama, Claude, Gemini, Grok).
* Implement semantic search, embeddings, and vector-based solutions.
* Integrate AI components using orchestration frameworks (LangChain, LangGraph, LlamaIndex).
* Ensure reliable deployment with Docker/Kubernetes and modern DevOps practices.
* Evaluate model performance using appropriate metrics and methodologies.
**Requirements:**
* 5+ years of overall engineering experience, including 1+ year in AI/ML.
* Strong proficiency in Python and Node.js (TypeScript).
* Practical experience with fine-tuning, deployment, and optimization of LLMs.
* Solid expertise in NLP, prompt engineering, embeddings, and semantic search.
* Experience working with vector databases (Pinecone, Weaviate, Faiss, etc.).
* Familiarity with orchestration frameworks for LLMs.
* Hands-on experience with Docker and Kubernetes.
* Good understanding of evaluation methods and metrics for LLMs