Junior Machine Learning Software Developer

1 dia atrás

São Paulo, São Paulo, Brasil beBeeMachine Tempo inteiro R$80.000 - R$120.000

We are seeking an innovative Junior Machine Learning Developer to conceptualize and execute clear, quality code for developing cutting-edge software solutions.

Key Responsibilities:
  • Create high-quality software using machine learning algorithms and frameworks like Python, NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
  • SUPPORT CUSTOMERS AND PARTNERS by troubleshooting any of their software issues.
  • Collaborate with our team to design and implement large language models and generative AI solutions.
  • Work on data pipelines and model deployment concepts, and collaborate with the team to ensure seamless integration of ML models into applications.
Requirements:
  • Bachelor's degree in Computer Science, Mathematics, Statistics, or related field.
  • Strong understanding of machine learning concepts, including supervised vs. unsupervised learning, regression, classification, and basic knowledge of deep learning frameworks.
  • Familiarity with large language models (LLMs) and generative AI, including Retrieval Augmented Generation (RAG) architecture.
  • Proficiency in Python programming language and experience with Git for version control.
  • Ability to write simple database queries to extract data for ML models and familiarity with relational databases like PostgreSQL or MySQL.
  • Strong problem-solving skills, eagerness to learn new challenges in machine learning, and proactive approach to seeking solutions.
  • Good spoken and written English is required.
Nice to Have:
  • DevOps & Cloud: Curiosity about deployment processes for ML models and cloud platforms, specifically services for generative AI like AWS Bedrock, Google Vertex AI, or Azure OpenAI Service / Azure Machine Learning Studio.
  • Basic understanding of Docker for containerizing ML applications.
  • Awareness of data privacy and security considerations in ML.
  • Any personal ML projects, Kaggle participation, or contributions to open-source ML initiatives.
Behavioral Skills:
  • Collaboration & Communication: Willingness to work effectively within a team and ability to clearly articulate thoughts and ask questions.
  • Problem Solving & Initiative: Eagerness to learn and tackle new challenges in machine learning and proactive in seeking solutions and asking for help when needed.
  • Adaptability & Continuous Learning: Strong desire to learn new ML technologies, algorithms, and research, and openness to feedback and continuous improvement.

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