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Senior Python AI / ML Engineer

Senior Python AI / ML Engineer

InteticsWorkFromHome, İstanbul, Türkiye
14 days ago
Job description

Overview

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 details and expectations are described below.

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.

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.
  • We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

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