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AI Expert - Agentic AI e Machine Learning

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Onsite

AI Expert - Agentic AI e Machine Learning

Aqua Capital

AI Expert - Agentic AI e Machine Learning

Skills

Google Cloud PlatformSQL QueriesBig DataDeep LearningPythonData ScienceJavaNumPypandasKerasPyTorchTensorFlowRData AnalysisMachine LearningAIAWSNLP / Natural Language ProcessingHadoopAzure

1 month ago

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Important information


Contract type:

Freelance / Contract

Location:

São Paulo, State of São Paulo, Brazil

Work mode:

Onsite

Published on:

20 September 2026

What they need


About The Role The AI Developer will use AI to drive value creation across portfolio companies — improving operational efficiency, decision-making, and financial performance.

What You'll Do

  • Design and implement ML models that address specific business challenges within portfolio companies.
  • Generate AI-driven insights that lead to actionable recommendations, increasing revenue or reducing costs.
  • Establish metrics to track the effectiveness of AI solutions and provide data-driven feedback for continuous improvement.
  • Work closely with cross-functional teams to align on AI initiatives and drive adoption.
  • Share AI best practices and insights across the team.

What We're Looking For

  • Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
  • 3+ years of experience in AI/ML development, with a proven track record of delivering AI projects in a business context.
  • Proficiency in Python, R, or Java; strong data skills (SQL, Pandas, NumPy) and experience with AI frameworks (TensorFlow, Keras, PyTorch).
  • Experience with data analysis and visualization; familiarity with cloud platforms (AWS, Google Cloud, Azure).
  • Strong problem-solving, communication, and collaboration skills; adaptable to changing project requirements.

Desirable

  • Experience in the private equity or investment sector.
  • Knowledge of financial modeling and performance metrics.
  • Contributions to open-source AI projects or publications in relevant journals.
  • Exposure to NLP, deep learning, computer vision, model optimization, or big data tools (Hadoop/Spark).

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