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Build and deploy AI models using Python, PyTorch/TensorFlow, and frameworks like LangChain and LlamaIndex; package models for production and collaborate on R&D.
Build and improve natural-language applications using Python, ML algorithms, and neural networks; analyze data and customer needs to deliver AI-driven solutions.
Mô tả công việc: Key Responsibilities Data Engineering Pipelines Build and maintain data pipelines for Amazon SP-API, Advertising API, and other e-commerce platforms. Collect and process product reviews, sales,…
Build and scale production-grade LLM applications and AI systems for enterprises, owning architecture, data pipelines, deployment, and MLOps with Python, PyTorch/TensorFlow, and cloud-native tools.
Build and deploy production-grade LLM applications and agentic systems for enterprise clients using Python, PyTorch/TensorFlow, and MLOps tooling.
Design, fine-tune, and deploy LLMs to automate business processes in a manufacturing environment, collaborating with cross-functional teams to scale AI solutions into production.
Build and deploy AI models using Python, PyTorch, and Hugging Face; develop generative AI and NLP solutions with FastAPI and OpenAI integrations.
Build and maintain web apps using React for the frontend and Django/Django REST Framework for the backend, integrating AI services and collaborating on healthcare research projects.
Develop and implement GenAI solutions using the Datapizza AI framework, focusing on RAG, AI agents, and speech-to-speech architectures for enterprise clients.
Build and deploy ML models (churn, pricing, fraud) and LLM-based agents for an insurer, using Python, AWS SageMaker, and NLP libraries.
Design and implement end-to-end AI solutions using Python, PySpark, Databricks, Postgres and open-source LLMs like Qwen, building data pipelines, RAG systems and AI agents for enterprise clients.
Build and scale data-driven and generative AI solutions for global clients in banking, pharma, and public sector using cloud platforms, Spark, and Azure OpenAI.
Build and maintain data pipelines, clean and structure financial data, and integrate GenAI solutions like LLMs and RAG for a banking-focused project using Python, SQL, and ETL/ELT.
Build and scale AI-driven products using LLMs, RAG pipelines, and vector databases with Rust or Golang, from prototype to production in rapid cycles.
Build and deploy production-grade AI systems end-to-end, from data pipelines and ML models to scalable deployment and monitoring using Python, PyTorch, and MLOps tools.
Build and deploy AI/ML systems for finance, using LLMs, prompt engineering, and neural networks with Python, TensorFlow/PyTorch, and cloud platforms.
Build and deploy Python-based backend services, integrate LLM APIs (OpenAI, Hugging Face), and fine-tune prompts for AI-driven applications.
Build and fine-tune large language models for Avito’s products, optimizing training pipelines and inference speed for production-scale NLP systems.
Build and deploy ML models and AI systems for enterprise clients, focusing on LLMs, NLP, and computer vision to solve industrial, automotive, and software-engineering challenges.
Lead the design and deployment of generative AI and agentic AI systems for healthcare, including LLMs, RAG, and AI agents, while ensuring responsible, scalable, and compliant solutions.
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