Senior Python AI/ML Engineer

Описание

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.