4 months ago
Mexico City, MexicoSenior
Responsibilities
- Deliver machine learning solutions on AWS for customers as part of a cross-functional team.
- Develop and implement machine learning models, MLOps capabilities, and analytics.
- Process big data and prepare training data for machine learning models.
- Design and document solutions developed by an architect.
- Participate in daily standups and bi-weekly customer agile ceremonies.
Requirements
- Strong experience building machine learning models for real-world applications.
- Strong experience with at least one of AWS ML Services/SageMaker, Keras, TensorFlow, PyTorch, Scikit-learn, MLflow, Kubeflow, Airflow, time-series forecasting, or inferential statistics.
- Strong experience with big-data or streaming platforms such as Spark and Hadoop, or with Python/Pandas, PySpark, Scala, and SQL for data processing and cleansing.
- Strong understanding of feature definition, model metadata, hyperparameter tuning, stochastic gradient descent, deep-learning layer types, and activation functions.
- Experience with visualization using SageMaker, ggplot, Matplotlib, or Seaborn.
- Experience with infrastructure-as-code tools such as CloudFormation, Amazon CDK, or Terraform.
- Excellent written and verbal communication skills.
Benefits
- 100% remote work.
- Medical insurance for employees and eligible dependents.
- Generous holidays and flexible paid time off.
- Competitive phantom equity, peer bonus awards, and paid exams and certifications.
- State-of-the-art laptop, tools, equipment, and office stipend.
- Individual professional development plan and annual learning and development stipend.
- Work with a worldwide team and supportive corporate culture.
- The role may require up to 25% travel depending on business needs.
- This is a future-opportunity talent pipeline rather than an active opening.
Tech Stack
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