Senior Machine Learning Model Developer

Há 4 dias

Brasil beBeeData Tempo inteiro R$120.000 - R$156.000
Machine Learning Engineer

About the Role:

We are seeking a highly skilled Machine Learning Engineer to join our team. As a key member of our engineering team, you will be responsible for developing and deploying machine learning models that drive business value.

Key Responsibilities:

  • Model Development & Deployment: Design, build, and deploy machine learning models using Python (Pandas, NumPy, scikit-learn, TensorFlow, PyTorch).
  • Time Series Forecasting: Apply advanced time series techniques (ARIMA, SARIMA, Prophet, LSTM/RNNs) to forecast and model temporal data.
  • MLOps: Build and manage ML pipelines for training, validation, deployment, and monitoring using tools like MLflow, Kubeflow, or cloud-based ML services.
  • Model Monitoring & Optimization: Track performance, detect drift or bias, and iterate on models to improve accuracy, reliability, and scalability.
  • Feature Engineering: Develop and select impactful features, especially for time series and structured datasets.
  • Exploratory Data Analysis & Visualization: Analyze datasets and communicate findings through clear visualizations (Matplotlib, Seaborn, Plotly) to guide decision-making.
  • Collaboration: Work with product managers, data scientists, engineers, and business stakeholders to align ML solutions with real-world needs.
  • (Bonus) Data Engineering: If you have strong SQL and ETL skills, help design and optimize data pipelines to ensure models have clean, reliable inputs.

Required Skills:

  • Advanced Python programming for ML (Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch).
  • Strong understanding of supervised, unsupervised, and deep learning techniques.
  • Expertise in time series forecasting and handling temporal data.
  • Experience with MLOps practices for production-scale deployments.
  • Familiarity with cloud ML services (AWS SageMaker, Azure ML, Google Cloud AI Platform).
  • Strong problem-solving and communication skills.

Preferred/Nice to Have:

  • Solid SQL skills and experience with data extraction/transformation.
  • Knowledge of modern data engineering tools (Airflow, Spark, dbt, Snowflake, or similar).
  • Experience with CI/CD for ML workflows.

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