Top Machine Learning Jobs in Tijuana

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.

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 Engineering Manager, you will lead the end-to-end machine learning lifecycle, from data collection to deployment. You'll implement novel techniques, mentor team members, and collaborate with cross-functional teams to ensure effective communication and innovation.

As part of the Sponsored Advertising team at Chewy, you will lead machine learning initiatives to enhance product search and ad relevance, collaborating with product leaders to develop and deploy models that improve user engagement and vendor visibility. Responsibilities include building predictive models and sharing insights with leadership.

The Director of Data Science and Machine Learning will lead the Machine Learning, Data Science, and Product Analytics teams, drive data-powered insights for product performance, and collaborate across departments to optimize business growth. Responsibilities include team leadership, defining strategic vision, fostering collaboration, and overseeing the development of ML and DS models.

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.

The AI Steward will oversee the data and development lifecycle related to Generative AI and Machine Learning, ensuring data compliance and governance. Responsibilities include establishing frameworks for AI compliance, collaborating with development teams, and resolving data issues to adhere to regulatory requirements.

As a Machine Learning Engineer II on the ML Fraud team at Affirm, you will develop models to predict fraud likelihood using proprietary and third-party data. You will collaborate across teams to improve fraud detection capabilities, implement data pipelines, and create innovative solutions for emerging fraud patterns, impacting financial performance significantly.