Top Machine Learning Jobs in Mexico

The Machine Learning Engineer will develop and deploy machine learning models at scale to analyze risks associated with various businesses, utilizing both structured and unstructured data from diverse sources. Collaborating closely with product management and software engineers, they will have full ownership of their projects and work within a two-week sprint framework.

The Machine Learning Engineer will lead the development and deployment of machine learning models to assess the risks associated with various businesses by analyzing structured and unstructured data from multiple sources.

As a Machine Learning Engineer at Kalepa, you will lead the development and deployment of machine learning models aimed at assessing business risks using diverse structured and unstructured data sources. You will drive project direction with complete ownership, collaborating closely with cross-functional teams in a two-week sprint environment.

The Machine Learning Infrastructure Engineer will drive ML infrastructure and operations, collaborating with ML Engineers and Data Scientists to support model development and deployment. Key responsibilities include building scalable infrastructure for model lifecycle management, creating an internal training platform, and deploying data stores for batch pipelines and real-time recommendations.

The Lead Data Science Analyst will manage advanced analytics initiatives, focusing on credit risk and home loans servicing. The role involves developing machine learning algorithms, collaborating cross-functionally to deliver insights, and creating reports and dashboards to monitor metrics. Additionally, the analyst will identify and implement efficiency improvements and continuously enhance their skills through training.

The Principal Machine Learning Engineer will drive the development and implementation of machine learning algorithms, collaborate with product and engineering teams, design architectures, conduct experiments, and guide emerging ML engineers, ensuring the effective integration of AI across Atlassian's products and services.

The Senior Principal Machine Learning Engineer will guide the development and deployment of advanced machine learning algorithms, collaborating closely with various teams to integrate AI functionalities across Atlassian products. Responsibilities include designing system and model architectures, conducting experiments, mentoring other ML engineers, and ensuring the effective use of AI in the product suite.

As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess business risk using large datasets from varied sources. You will work in agile sprints and collaborate with Product Management and Software Engineers, taking full ownership of your projects.

As a Machine Learning Engineer on the On-Device ML team, you will design and prototype new features, build and implement ML models, collaborate with product teams, and launch and monitor model deployments, all aimed at enhancing Grammarly's writing assistance capabilities on devices.

The Senior Machine Learning Engineer will lead the framing, development, and deployment of machine learning models to analyze risks for various types of businesses. The role involves processing large datasets from diverse sources and requires collaboration with Product Management and Software Engineers.

You will build Cash App's customer support chatbot, utilize smart tooling, engineering high-throughput ML models and mentor other team members. You'll work with Product, Design, and Engineering teams to enhance customer support experiences through advanced machine learning techniques.

Lead a team of machine learning engineers and software engineers to develop models and embedding evaluation to improve ranking for ads and content. Define architecture of the embedding platform while ensuring quality, scalability, and drive rapid iterations. Conduct design and code reviews.

The Staff Machine Learning Engineer will lead the development of a marketing experimentation platform, working with cross-functional teams to design scalable ML products for optimization and ROI measurement. Responsibilities include system architecture, stakeholder collaboration, and improving ML engineering practices.

The Machine Learning Engineer will lead the development and deployment of machine learning models to assess business risk by transforming large datasets into valuable insights. Responsibilities include ownership of projects, collaboration with product management and software engineers, and operating within a two-week sprint methodology.

The Senior Machine Learning Scientist will lead the development of machine learning algorithms, collaborate with cross-functional teams on data fusion problems, design neural network architectures, manage research projects, and optimize software for performance. They will also stay current on advancements in machine learning and contribute to novel algorithm development.

The Senior Machine Learning Engineer will partner with product and marketing teams to enhance customer experiences and drive growth. Responsibilities include building and deploying machine learning models specializing in personalization for Cash App and Afterpay. The role emphasizes creativity, collaboration, and leveraging large transaction datasets for innovative AI applications.

Computer Scientists will work in a classified environment employing various scientific techniques to analyze intelligence data and assist in the development of OSINT capabilities. Responsibilities include integrating algorithms, maintaining databases, and creating briefs for senior leadership.