About the role

Design, implement, and optimize machine learning models for production environments while collaborating with cross-functional teams. Develop and maintain ML pipelines, including model training, validation, and deployment, while monitoring performance.

What they look for

Python TensorFlow PyTorch Scikit-learn Machine learning algorithms Statistics Probability Data preprocessing Feature engineering Model evaluation AWS GCP Azure Docker Kubernetes MLOps

Requirements

Requires a bachelor's degree in a technical field and strong proficiency in Python and ML frameworks. Candidates must have solid understanding of machine learning algorithms and the ability to work in a US time zone.

Benefits

Competitive pay Remote work Paid holidays Paid time off Performance bonus

Full description

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 ROLEWe 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