Ingeniero de Machine Learning — Sistemas Adaptativos Remotos

Placements24; Tijuana; Hybrid; MXN 600,000 - 1,000,000; Full time

Benefits offered by this job

Competitive salary

Health benefits

Remote work from anywhere in Mexico

Professional development opportunities

Collaborative remote culture

Job summary

Placements24 is seeking a talented Machine Learning Engineer for a fully remote role in Mexico. You will design, develop, and deploy ML models for adaptive learning systems, work with large datasets, and build scalable pipelines in a collaborative R&D setting.

Ideal candidates hold a Master’s or PhD in CS/ML and have 3+ years of hands-on ML experience, strong Python skills, and familiarity with cloud platforms and MLOps practices.

Qualifications

• Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field.
• 3+ years hands-on experience in developing and deploying ML models.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Experience with data manipulation (Pandas, NumPy).
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps is a plus.

Responsibilities

• Develop and implement ML algorithms and models for adaptive systems.
• Build, train, and evaluate ML models using large datasets.
• Design and maintain scalable ML pipelines for data processing, feature engineering and deployment.
• Collaborate with product managers and software engineers to deploy models in production.
• Research new ML techniques to improve performance and efficiency.
• Monitor and optimize deployed ML models and data integrity.
• Write clean, well-documented Python code and stay current with ML advances.
• Participate in code reviews and share knowledge within the team.

Skills

Python

Machine Learning

Remote collaboration

Education

MS/PhD in CS/ML

Tools

TensorFlow

PyTorch

Scikit-learn

Pandas

NumPy

Job description

Placements24 is seeking a talented Machine Learning Engineer for a fully remote role in Mexico. You will design, develop, and deploy ML models for adaptive learning systems, work with large datasets, and build scalable pipelines in a collaborative R&D setting.

Ideal candidates hold a Master’s or PhD in CS/ML and have 3+ years of hands-on ML experience, strong Python skills, and familiarity with cloud platforms and MLOps practices.