استخدام AI Software Engineer

هوش سازه | Hoosh Sazeh
تهران، تهران

Key Responsibilities

Autonomous Systems: Design and implement Agentic AI frameworks capable of multi-step reasoning, tool-use, and complex task execution (e.g., using LangGraph, CrewAI, or AutoGen).
LLM & RAG Architectures: Build and optimize Large Language Model (LLM) solutions, focusing on advanced RAG (Retrieval-Augmented Generation) pipelines and fine-tuning strategies.
End-to-End Modeling: Develop, train, and deploy Machine Learning and Deep Learning models to extract insights from diverse data streams and temporal patterns.
Operational Excellence (MLOps/LLMOps): Establish and maintain robust pipelines for model monitoring, versioning, and automated deployment (CI/CD for ML).
System Integration: Transform experimental models into scalable, maintainable, and high-performance APIs and microservices.

· Architecture Innovation: Stay at the forefront of AI research to implement and adapt

Technical Requirements

Professional Experience: Minimum 2+ years of proven experience in AI/ML engineering roles.
Time-Series Expertise: Deep knowledge of Time-Series Analysis and forecasting using both statistical methods and modern neural networks (RNNs, LSTMs, TCNs, or TS-Transformers).
Core ML/DL Mastery: Comprehensive understanding of Machine Learning and Deep Learning theory—must be able to explain the "why" behind architectures and optimization techniques.
Python & Development: Expert proficiency in Python and experience building web services using Django or Flask.
Database Expertise: Proficiency in working with both traditional databases (SQL/NoSQL) and modern Vector Databases (e.g., Pinecone, Milvus, Qdrant, or Weaviate) for semantic search.
Engineering Standards: Strong commitment to Clean Code, SOLID principles, and design patterns to ensure team-friendly and maintainable codebases.
DevOps for AI: Solid experience with Git, Docker, and the principles of MLOps/LLMOps to ensure model reliability in production.

Preferred Traits

Advanced Problem Solver: A proactive mindset with the ability to break down complex, ambiguous business problems into executable technical solutions.
Researcher-Developer Hybrid: The ability to read and implement state-of-the-art research papers while following software engineering best practices.
Detail-Oriented: Passionate about code quality, performance optimization, and rigorous testing of AI systems.
English Proficiency: Strong ability to communicate technical concepts and stay updated with global AI advancements.

تمام وقت

۱۴۰۴/۱۲/۰۲ (منقضی‌شده)

مشاغل مشابه