Remote ML Engineer — Build & Deploy Scalable Models

BairesDev; United States; Remote; MXN 1,676,000 - 2,235,000; Full time

Benefits offered by this job

100% remote work

Hardware & software setup

Flexible hours

Paid time off & holidays

Job summary

BairesDev is looking for a Machine Learning Engineer to design, build, and deploy scalable ML solutions that turn data into actionable insights. This 100% remote role offers competitive compensation in USD or your local currency, flexible hours, and hardware/software support for a home office.

You will work with diverse global teams to develop models, pipelines, feature engineering, and production-grade systems, review code, document processes, and communicate findings to stakeholders.

Qualifications

• 3+ years of experience in machine learning engineering or related fields.
• Strong knowledge of machine learning algorithms and statistical methods.
• Proficiency in Python and experience with ML frameworks and libraries.
• Experience with data processing and feature engineering techniques.
• Familiarity with cloud platforms and containerization technologies.
• Advanced level of English.

Responsibilities

• Build and train machine learning models for various business applications.
• Develop and maintain ML pipelines for data processing and model deployment.
• Collaborate with data scientists to implement algorithms and optimize model performance.
• Monitor and improve existing ML systems to ensure accuracy and reliability.
• Participate in code reviews and contribute to ML best practices across the team.
• Document technical processes and communicate findings to stakeholders.

Skills

Machine learning

Python

Cloud platforms

Containerization

Data processing

Feature engineering

English proficiency

Tools

TensorFlow

PyTorch

Scikit-Learn

Job description

BairesDev is looking for a Machine Learning Engineer to design, build, and deploy scalable ML solutions that turn data into actionable insights. This 100% remote role offers competitive compensation in USD or your local currency, flexible hours, and hardware/software support for a home office.

You will work with diverse global teams to develop models, pipelines, feature engineering, and production-grade systems, review code, document processes, and communicate findings to stakeholders.