Senior Data Scientist (GenAI & Machine Learning)
New
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- AWSPythonSQLPyTorchAzureTensorflowGenerative AILangChain
Requirements
- Strong experience in Python and SQL for data science and machine learning applications.
- Solid background in Machine Learning, including supervised and unsupervised learning techniques.
- Hands-on experience with Generative AI, LLMs, and RAG-based architectures.
- Experience with frameworks such as LangChain and/or LangGraph.
- Knowledge of vector databases such as OpenSearch or similar technologies.
- Proficiency with data science and ML libraries such as Pandas, Scikit-learn, TensorFlow, and/or PyTorch.
- Experience working in cloud environments (AWS and/or Azure).
- Strong understanding of model evaluation metrics and AI system performance analysis.
- Experience deploying and maintaining production-grade AI/ML systems.
- Familiarity with MLOps practices, monitoring, and CI/CD pipelines for ML (differential).
- Experience with distributed systems, containerization, and serverless architectures (differential).
- Exposure to Computer Vision solutions (differential).
- Experience with AWS Bedrock, OpenAI, or Azure Document Intelligence (differential).
- Experience working in agile environments such as Scrum or Kanban (differential).
Responsibilities
- Develop, train, and deploy Machine Learning and Generative AI models for production environments.
- Design and implement LLM-based solutions, including Retrieval-Augmented Generation (RAG) architectures.
- Build and maintain scalable data pipelines for text processing using vector databases and modern data frameworks.
- Develop AI-driven applications and APIs using tools such as LangChain, LangGraph, OpenAI, and AWS Bedrock.
- Design and implement Computer Vision solutions, including image classification, object detection, and semantic segmentation.
- Ensure performance, scalability, security, and reliability of AI systems in production.
- Work with cloud platforms such as AWS and Azure to deploy and manage AI solutions.
- Evaluate and optimize models based on metrics such as accuracy, latency, cost, and relevance.
- Collaborate with Product Owners and stakeholders to define technical approaches and AI strategies.
- Participate in agile ceremonies and work in cross-functional, multidisciplinary teams.
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