Generative AI Engineer

1 dia atrás

Remoto, Brasil Animati Tempo inteiro R$120.000 - R$240.000 por ano
REMOTE
Main Responsibilities
  • Design, train, and fine-tune generative and agentic AI models for SaaS applications.
  • Develop scalable APIs to integrate AI models into workflows.
  • Build LLMOps pipelines for model deployment, monitoring, and optimization.
  • Use frameworks such as AutoGen, CrewAI, LangGraph, and LangChain for advanced solutions.
  • Collaborate with internal teams and group companies to deliver customized solutions.
  • Research and apply new techniques to improve AI performance and capabilities.
  • Document processes, ensure reproducibility, and promote responsible AI practices.
Benefits
  • Work directly with portfolio companies to drive innovation and generate real impact.
  • Leverage cutting-edge AI tools to accelerate full stack development.
  • Be part of a high-performance team within a long-term investment company.
  • Competitive compensation package, benefits, and professional growth opportunities.
Required Knowledge
  • Degree in Data Science, Computer Science, Engineering, or related fields;
  • Solid experience with Python, PyTorch, TensorFlow, and Hugging Face (minimum 3 years);
  • Hands-on experience with development, fine-tuning, and deployment of generative and agentic models;
  • Knowledge of cloud platforms (preferably Azure) and distributed computing;
  • Experience with MLOps frameworks (e.g., MLFlow, Azure ML) and LLMOps;
  • Familiarity with agentic frameworks (AutoGen, CrewAI, LangGraph, LangChain);
  • Fluency in English (spoken and written) for communication in a global environment.
Desired Knowledge
  • Experience with multimodal AI (e.g., text-to-image and text-to-video generation);
  • Knowledge of advanced fine-tuning techniques (LoRA, adapters);
  • Deep understanding of agentic AI applied to SaaS.
Skills
  • Critical thinking and solving complex problems;
  • Clear technical communication with multidisciplinary teams;
  • Initiative in researching and applying advanced techniques;
  • Ethical responsibility and reproducibility in solutions;
  • Adaptability to dynamic environments.
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