Machine Learning Engineer

Summary

Join our multinational team as a Machine Learning Engineer! Design and implement machine learning models to solve real-world business challenges. You will need strong Python, TensorFlow, PyTorch, Scikit-learn, AWS, Azure ML, and Kubernetes expertise, along with experience deploying ML solutions. This is a 100% remote, full-time independent contractor position, requiring 5+ years of experience and advanced English fluency. The role is expected to open soon, but joining our talent pool offers an advantage. We are open to negotiating the monthly rate.

Requirements

• +5 years of experience with the role
• Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Experience with cloud platforms (AWS, Azure ML) for deploying ML solutions
• Knowledge of Kubernetes for container orchestration and scaling ML workloads
• Familiarity with data pipelines, feature engineering, and model evaluation techniques
• Experience deploying and monitoring ML models in production environments
• Strong problem-solving skills and ability to work in an agile environment
• Advanced written and spoken English fluency is a must have
• Bilingual applicants (Spanish or Portuguese native and English advanced fluency) currently located in Latin America

Responsibilities

• Develop and optimize machine learning models to address business problems
• Implement, test, and deploy ML algorithms using frameworks like TensorFlow, PyTorch, and Scikit-learn
• Work closely with data scientists and engineers to transform research prototypes into scalable solutions
• Optimize model performance, scalability, and efficiency for deployment in cloud and on-premise environments
• Deploy and manage ML models using AWS, Azure ML, and Kubernetes
• Monitor model performance, retrain as needed, and ensure reliability in production
• Collaborate with cross-functional teams to integrate ML models into business applications

Preferred Qualifications

• Experience with MLOps practices and tools
• Understanding of big data processing frameworks (Spark, Dask, etc.)
• Knowledge of CI/CD pipelines for ML model deployment
• Familiarity with deep learning architectures and NLP techniques

Benefits

• 100% remote
• Full-time, Monday to Friday (8 hours a day, 40 hours a week)
• Time zone: US time zones (PST, MST, CST, or EST)