Machine Learning Engineering Associate - Remote

Overview

We are looking for an innovative and passionate Machine Learning Engineer Associate to join our fast-paced, dynamic team. As a key member of our technology division, you will play a vital role in developing, deploying, and optimizing end-to-end machine learning models. This role demands expertise in MLOps (Machine Learning Operations), Data Science, Data Analisys and the ability to handle the entire machine learning lifecycle—from data ingestion to model deployment and beyond.

As a Machine Learning Engineer at Oppizi, you will have the opportunity to collaborate with cross-functional teams, including software engineers and product managers, to deliver high-quality ML solutions that directly impact business outcomes. You will also be responsible for ensuring that our models are scalable, efficient, and aligned with the company’s goals.

In Short

• Model Development and Deployment: Design, implement, and deploy machine learning models that address business needs, ensuring high availability and performance in production environments.
• MLOps and Automation: Apply MLOps best practices to automate the ML lifecycle, including data ingestion, training, and deployment pipelines. Build and maintain CI/CD pipelines for continuous integration and delivery.
• Performance Monitoring and Optimization: Monitor deployed models to ensure they meet performance metrics, and continuously improve them for accuracy and scalability.
• Collaboration and Communication: Work closely with software engineers, product managers, and other stakeholders to develop and communicate ML solutions effectively.

Requirements

• Strong understanding of machine learning algorithms and frameworks.
• Experience with MLOps tools and practices.
• Proficiency in programming languages such as Python or R.
• Familiarity with data processing and analysis tools.
• Ability to work in a collaborative team environment.

Benefits

• Opportunity to work on innovative projects.
• Collaborative and dynamic work environment.
• Professional development opportunities.