Top Machine Learning Jobs in Mexico City
Lead a team of machine learning engineers in developing a personalized video recommendation engine. Responsibilities include defining system architecture, conducting A/B testing, performing design reviews, and optimizing performance metrics to improve the recommender system.
As a Principal Machine Learning Engineer, you will lead the technical roadmap for Snap's Ad Marketplace, designing and scaling machine learning models to enhance ad efficiency, collaborate with teams on machine learning strategies, and ensure operational excellence throughout the system.
As a Machine Learning Engineer, you will lead the design, development, and deployment of machine learning models to assess risk for businesses. You will utilize vast amounts of structured and unstructured data from various sources to generate insights. Team members manage their own projects and collaborate closely with product management and software engineers in a sprint-based environment.
In this role, the Senior Manager of Machine Learning will lead a team focused on developing machine learning solutions for fraud prevention in the financial services sector. Responsibilities include team management, performance evaluation of models, and collaboration with various teams to enhance customer experience and business profitability.
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.
As a Senior Machine Learning Engineer at TrueML, you'll architect and implement ML infrastructure, develop production-grade ML pipelines, and maintain systems for real-time and batch decision-making. You'll collaborate with data engineers and data scientists to scale algorithms and ensure robust deployment of machine learning models.
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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.
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.
As a Principal Engineer in ML/AI, you will lead technical efforts across teams, drive product development, set engineering standards, and provide mentorship while collaborating closely with various stakeholders to enhance and innovate financial services.
The Principal Engineer will lead efforts in machine learning and AI, collaborating with teams to build impactful products, setting technical standards, and mentoring others. Responsibilities include hands-on development, technical leadership, and influencing hiring and coding practices.
This role involves leading product releases at Metropolis by developing and executing robust testing and release plans. The Product Operations Manager will collaborate with Product Managers and cross-functional teams to drive product adoption, communicate updates, and assess product impact based on data and feedback.
As a Principal Machine Learning Engineer, you will lead the development of prediction or optimization engines for advertising platforms, driving innovation through AI and machine learning. Responsibilities include designing ad algorithm architecture, developing scalable data analysis methods, and collaborating with cross-functional teams.
The Lead Software Engineer will develop and enhance Disney's advertising machine learning platform, focusing on improving inventory forecasting, ad delivery, pricing, and targeting using AI. This role involves creating scalable solutions for data analysis and modeling while collaborating with researchers and balancing architectural considerations.
Lead the development and optimization of algorithms for personalization and recommendation systems at Disney, driving and enabling ML usage across multiple domains. Collaborate with stakeholders to identify new opportunities while maintaining robust production deployment and high system reliability.
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.
As a Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess risks for various businesses, utilizing structured and unstructured data sources. You will own projects and collaborate closely with Product Management and Software Engineers within a two-week sprint framework.
The Senior Machine Learning Engineer will lead the development and deployment of machine learning models to assess business risk. Responsibilities include handling large volumes of both structured and unstructured data to derive insights, with full ownership of projects in a fast-paced team environment.
Kalepa is seeking a Machine Learning Engineer to lead the development, framing, and deployment of machine learning models to analyze risk across different classes of businesses. Responsibilities include turning structured and unstructured data into insights and collaborating closely with Product Management and Software Engineers.
As an Application Engineer, you will oversee design and implementation of assigned products, manage risks, analyze and deploy new user stories, guide junior engineers, and enforce IT standards. Collaboration with various stakeholders is crucial for achieving team commitments and ensuring high reliability of solutions.
As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess risks for various businesses, utilizing structured and unstructured data. You will have ownership of projects and collaborate closely with Product Management and Software Engineers in a two-week sprint cycle.
As a Machine Learning Engineer at Kalepa, you will develop and deploy machine learning models to assess the risk associated with various businesses. You will utilize structured and unstructured data, work closely with Product Management and Software Engineers, and have full ownership over project direction in a sprint-based team environment.
As a Machine Learning Engineer at Kalepa, you will be responsible for leading the development and deployment of machine learning models to assess business risks. You will analyze large datasets from various sources to extract insights and are expected to own and drive your projects within a sprint-based framework in collaboration with Product Management and Software Engineers.
As a Machine Learning Engineer at Kalepa, you will lead the design, development, and deployment of machine learning models to evaluate business risks. Handling both structured and unstructured data, you'll generate insights and collaborate with product and software teams to drive project direction in a fast-paced environment.
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