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
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