Top Machine Learning Jobs in Mexico City

Lead a team of engineers in developing a personalized video recommendation engine. Define the architecture for scalability and performance, conduct A/B testing, and improve the recommendation system through technical reviews and team mentorship.

Lead the technical direction of the Ad Ranking team at Snap, focusing on advancing ML capabilities for ad optimization. Design and scale machine learning models, collaborate with cross-functional teams, and stay current with ML technologies to solve complex advertising-related problems.

As a Principal Machine Learning Engineer, you will drive the technical roadmap of Snap's Ad Marketplace and Pacing teams, design and scale machine learning models for optimal ad delivery, and collaborate with cross-functional teams. You will stay updated on the latest in machine learning to solve complex problems, advocate for best practices, and provide technical direction to influence the ML community.

The Lead Machine Learning Engineer will focus on developing and optimizing algorithms for Hulu's recommendation and personalization systems. Responsibilities include collaborating with product and data teams, maintaining existing models, and establishing best practices in algorithm development and deployment.

The Staff Machine Learning Engineer will enhance batch inference services and tooling for financial crime detection, work on infrastructure for model development, and lead AI/ML initiatives within Cash App. Responsibilities include collaborating with various teams, developing prototypes, and driving strategic roadmaps.

The Senior Machine Learning Engineer will design and build services for ML modelers, integrate data streams to create efficient models, and lead MLOps initiatives. The role involves collaborating with various teams to enhance ML tools and infrastructure while maintaining production software and developing new solutions.

The Director of Machine Learning Operations will lead the ML Ops team to develop, implement, and oversee machine learning strategies. Responsibilities include managing ML infrastructure, deploying models, ensuring performance and scalability, and collaborating with cross-functional teams to integrate ML solutions into the advertising technology platform.

The Machine Learning Engineer will focus on enhancing search relevance and personalization on Instacart's platform by developing and optimizing machine learning models. Collaboration with cross-functional teams is vital to create scalable solutions while also contributing to research and thought leadership.

As a Machine Learning Engineer at Kalepa, you will lead the development and deployment of machine learning models to gauge business risks, utilizing diverse data sources. You'll have full project ownership and collaborate closely with Product Management and Software Engineering teams in an agile environment.

As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to analyze risk across various business classes, utilizing extensive structured and unstructured data. You will work closely with Product Management and Software Engineers within an agile environment to drive project ownership and direction.

As a Senior Machine Learning Engineer, you'll lead the development and deployment of machine learning models to analyze business risks. You'll handle structured and unstructured data to derive insights and work closely with product and software teams while managing your project ownership.

As a Machine Learning Engineer at Kalepa, you will lead the development and deployment of machine learning models to assess risk across various business classes. You will convert large volumes of structured and unstructured data into actionable insights, working closely with Product Management and Software Engineers over two-week sprints.

As a Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess the risk of various businesses by analyzing structured and unstructured data from multiple sources, including web data and satellite imaging.

The Machine Learning Engineer will lead the development and deployment of machine learning models to assess the risk of various business classes. Responsibilities include analyzing structured and unstructured data to derive insights and ensuring project ownership and direction within a two-week sprint cycle.

As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess business risk, utilizing both structured and unstructured data. You will work closely with Product Management and Software Engineers in an agile environment, taking ownership of your projects to drive their direction and execution.

The Senior Machine Learning Engineer at Kalepa will lead the development and deployment of machine learning models to assess business risk using structured and unstructured data. Responsibilities include project ownership, collaboration with product managers and software engineers, and working within a two-week sprint cycle.

The Senior Machine Learning Engineer will lead the development and deployment of machine learning models to analyze business risks. This role requires turning large volumes of structured and unstructured data into actionable insights while managing project direction and collaborating with teams on a two-week sprint cycle.