The Role
Design, implement, and optimize production-ready machine learning models and pipelines. Collaborate with data, software, and product teams to integrate ML solutions. Perform data preprocessing, feature engineering, EDA, training, validation, deployment, and monitoring. Maintain environment setup, scalable APIs, and database architecture. Document work and stay current with ML research and best practices.
Summary Generated by Built In
Pomelo AI places the best offshore AI talent with leading tech companies across the globe. We enable hard-working and ambitious talent to work remotely from their home countries, while gaining exposure into how the world’s top companies operate.
ABOUT THE ROLE
ABOUT THE ROLE
We are seeking an experienced Machine Learning Engineer to design, develop, and deploy machine learning models for real-world applications. The ideal candidate is passionate about AI, has strong software engineering skills, and can translate business or research requirements into production-ready solutions. This is a hands-on engineering role, where you’ll work on environment setup, scalable API design, and database architecture.
KEY RESPONSIBILITIES
- Design, implement, and optimize machine learning models for production environments
- Collaborate with data engineers, software engineers, and product teams to integrate ML solutions
- Perform data preprocessing, feature engineering, and exploratory data analysis
- Develop and maintain ML pipelines, including model training, validation, and deployment
- Monitor model performance and implement improvements or retraining as needed
- Stay up-to-date with the latest ML research, techniques, and best practices
- Contribute to technical documentation and knowledge sharing
QUALIFICATIONS
- Bachelor’s degree in a technical field
- Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Solid understanding of machine learning algorithms, statistics, and probability
- Experience with data preprocessing, feature engineering, and model evaluation
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) is a plus
- Ability to write clean, maintainable, and well-documented code
- Excellent problem-solving skills and ability to work independently or in a team
- Ability to work in a US time zone, Monday to Friday (8 hours per day)
NICE-TO-HAVES
- Master’s or PhD in Computer Science, Machine Learning, or a related field
- Experience in NLP, computer vision, recommendation systems, or reinforcement learning
- Exposure to MLOps tools and workflows
BENEFITS
- Competitive pay, always in US dollars
- Work remotely from the comfort of your home
- Paid holidays and time off
- Performance bonus
- Global exposure to the world’s best companies
Skills Required
- Bachelor's degree in a technical field
- Strong proficiency in Python
- Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Solid understanding of machine learning algorithms, statistics, and probability
- Experience with data preprocessing, feature engineering, and model evaluation
- Develop and maintain ML pipelines including training, validation, and deployment
- Ability to write clean, maintainable, and well-documented code
- Excellent problem-solving skills and ability to work independently or in a team
- Ability to work in a US time zone, Monday to Friday (8 hours per day)
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)
- Master's or PhD in Computer Science, Machine Learning, or related field
- Experience in NLP, computer vision, recommendation systems, or reinforcement learning
- Exposure to MLOps tools and workflows
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The Company
What We Do
Pomelo builds the infrastructure for the next generation of financial products, powering card issuance, processing, and payment operations across Latin America with an API-first platform.
