Senior Machine Learning Engineer
New
J
JobgetherMachine learning
Remote work opportunity within Brazil.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- Proven professional experience developing and deploying machine learning solutions using Python in production environments.
- Required Skills
- PythonPyTorchscikit-learnMLOps
Requirements
- Have professional experience developing and deploying machine learning solutions using Python in production environments.
- Have strong experience with PyTorch and hands-on machine learning model development.
- Have practical experience with AWS SageMaker, including Jobs, Pipelines, Model Registry, and GPU-based workloads.
- Understand MLOps practices, including model and experiment versioning, reproducibility, deployment, and governance.
- Have experience with statistical validation and model comparison, including assessing model consistency and performance.
- Bring strong analytical and problem-solving skills and a hands-on approach to investigating technical challenges and improving ML systems.
- Work collaboratively in a technically sophisticated, AI-focused environment and maintain ownership of deliverables.
- PyTorch Geometric and Graph Neural Networks (GNNs) experience is a plus.
- Knowledge of NetworkX, scikit-learn, and FAISS is an advantage.
- Machine learning model explainability experience is a plus.
Responsibilities
- Industrialize the core machine learning model of a Voice of the Customer platform, moving models from experimentation into reliable production environments.
- Transform notebook-based machine learning solutions into scalable, parametrized, production-ready pipelines on AWS.
- Structure and maintain the MLOps lifecycle, including model versioning, reproducibility, governance, and experiment management.
- Develop and manage training and inference pipelines using Amazon SageMaker, including Jobs, Pipelines, Model Registry, and GPU-based workloads.
- Perform statistical validation to assess score parity and consistency between existing models and production-migrated versions.
- Contribute to the evolution of a VoC platform that integrates data from multiple channels to generate business insights.
- Collaborate on technical and analytical initiatives to improve the reliability, scalability, and operational maturity of machine learning solutions.
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