Senior Python AI/ML Engineer
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. Originally posted on Himalayas