استخدام Senior AI/ML Engineer – GenAI

شرح موقعیت شغلی

• Design, develop, and deploy Generative AI applications using foundation models such as GPT, Claude, Gemini, Llama, Mistral, and other open-source LLMs.
• Build advanced RAG solutions using vector databases, embeddings, semantic search, reranking techniques, and hybrid search architectures.
• Develop prompt engineering strategies, evaluation frameworks, guardrails, hallucination mitigation techniques, and LLM optimization approaches such as LoRA, QLoRA, PEFT, and reinforcement learning.
• Integrate LLMs with enterprise applications, APIs, databases, internal tools, and business workflows.
• Design and implement autonomous and semi-autonomous AI agents with reasoning, planning, memory management, tool usage, and workflow orchestration capabilities.
• Build multi-agent systems using frameworks such as LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, MCP, A2A, or similar technologies.
• Develop agent collaboration patterns, task decomposition mechanisms, monitoring, observability, governance, and evaluation frameworks.
• Build and maintain end-to-end ML pipelines, including data ingestion, feature engineering, model training, evaluation, deployment, monitoring, model versioning, experiment tracking, and automated retraining.
• Develop predictive models, recommendation systems, anomaly detection solutions, NLP applications, and deep learning models.
• Design CI/CD pipelines for machine learning, Generative AI, and AI-powered applications.
• Deploy and manage AI workloads using Docker, Kubernetes, and cloud-native services.
• Monitor model drift, performance degradation, latency, data quality, and production reliability.
• Build scalable inference services and APIs for real-time and batch processing workloads.
• Architect cloud-native AI solutions on AWS, Azure, or Google Cloud Platform.
• Use managed AI services such as AWS SageMaker, AWS Bedrock, Azure OpenAI, Azure ML, Vertex AI, and similar platforms.
• Design scalable data and AI architectures using distributed computing platforms such as Databricks, Spark, Ray, and BigQuery.
• Optimize cloud infrastructure for performance, security, scalability, reliability, and operational cost.
• Establish AI governance, model lifecycle management, responsible AI practices, secure AI development standards, auditability, and compliance controls.
• Collaborate with data scientists, software engineers, data engineers, product managers, and business stakeholders to deliver production AI solutions.

• Upper C1 or higher English proficiency, both written and verbal.
• 7+ years of experience in software engineering, machine learning, artificial intelligence, or related technical roles.
• Minimum 3+ years of hands-on experience developing and deploying Generative AI applications in production environments.
• Strong Python programming skills with experience building scalable backend systems and production-grade AI applications.
• Extensive experience with PyTorch, TensorFlow, scikit-learn, and Hugging Face.
• Proven experience developing RAG architectures, knowledge retrieval systems, Agentic AI solutions, and multi-agent workflows.
• Strong understanding of vector databases, embeddings, semantic search, hybrid search, reranking, and retrieval optimization.
• Experience integrating LLMs with APIs, databases, enterprise applications, and business workflows.
• Strong understanding of MLOps, CI/CD, containerization, model deployment, monitoring, and model lifecycle management.
• Hands-on experience with Docker, Kubernetes, and cloud-native deployment patterns.
• Experience with cloud platforms including AWS, Azure, or Google Cloud Platform.
• Experience with managed AI services such as AWS SageMaker, AWS Bedrock, Azure OpenAI, Azure ML, or Google Vertex AI.
• Experience with distributed computing and data platforms such as Databricks, Apache Spark, Ray, BigQuery, or similar technologies.

• Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Qdrant, or similar technologies.
• Experience with AI orchestration and agent frameworks such as LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, MCP, or A2A.
• Experience with AI governance, responsible AI, model monitoring, auditability, compliance controls, LLM evaluation, hallucination detection, prompt testing, benchmarking, and production AI observability.
• Experience with recommendation systems, personalization, forecasting, anomaly detection, NLP, deep learning, real-time inference, or batch inference systems.
• Familiarity with DevOps practices, infrastructure-as-code, cloud automation tools, and agile development environments.

مهارت‌های مورد نیاز

• Pytorch
• Ai
• Docker

حداقل سابقه کار

• بیش از شش سال

حقوق

• حقوق از ۱۷۰,۰۰۰,۰۰۰ تومان

جنسیت

• مهم نیست

وضعیت نظام وظیفه

• مهم‌ نیست

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