Top Machine Learning Jobs in Mexico
As a Machine Learning Engineer at WeRide, you will work on developing and enhancing predictive modeling and anomaly detection within autonomous driving technologies. Collaborating with a team, you will implement active learning strategies and distributed learning algorithms to tackle complex problems and advance mobility solutions.
The Senior Data Scientist will focus on Pricing Optimization Analytics, conducting extensive data analysis to drive financial benefits and evaluate pricing strategies. This includes performing various analytics like causal inference and sensitivity analysis, aimed at improving decision-making within PayPal's monetization framework.
As a Data Scientist, you will lead efforts to enhance developer experience with PayPal's products by conducting data science projects. You will analyze product flows and use statistical methods to provide insights that inform the product roadmap for optimizing the developer journey.
The Senior Data Scientist will lead AI/ML projects by applying statistical modeling and machine learning to optimize promotional strategies, analyze customer data, and enhance decision-making with actionable business insights. This role involves developing predictive models, collaborating with cross-functional teams, and communicating findings effectively to business partners.
As a Data Engineer, you will build and operationalize complex data solutions, analyze data sources, design data solutions, and collaborate with teams to enhance data products. You'll leverage your analytical skills to modernize data practices and ensure data quality.
As a Finance Data Scientist at Genesys, you will utilize advanced machine learning and statistical techniques to drive data-driven decisions, optimize revenue streams, and improve operational efficiency. Your role includes developing and deploying models, collaborating with cross-functional teams, and ensuring model interpretation and performance evaluation to inform business strategy.
The Head of Enterprise Data Technology is responsible for defining and executing the technical strategy for data and analytic needs at M&T Tech. This leader works with stakeholders to develop an enterprise data roadmap, integration strategies, and centralized data solutions while interacting with senior leaders to align data initiatives with corporate objectives.
The Lead Data Scientist, ITS will develop and refine predictive models, collaborate with cross-functional teams to gather requirements, and drive data products to production. This role involves creating algorithms to solve business problems, conducting experiments to identify data anomalies, and leading projects to deliver data-driven results.
Featured Jobs
The Staff Data Scientist on the Anti-Cheat team will develop models and maintain automated systems to detect and mitigate cheating in games. Responsibilities include analyzing challenges, designing feature sets, mentoring junior staff, optimizing ETL pipelines, and collaborating with stakeholders and data engineers.
As Sr. Director of Analytics at MERGE, you will lead analytics initiatives to improve media and digital investments, guide a team in implementing analytics frameworks, and leverage data-driven insights for enhanced user experiences. You will strategize around performance measurement, oversee tagging and tracking, and develop actionable recommendations to support client objectives.
The Sr. Director of Analytics will lead analytics initiatives to enhance client media and digital investments by implementing frameworks, measuring performance, and providing data-driven insights. This role involves overseeing a team, driving service evolution, and developing client-specific strategies to improve user experience and marketing effectiveness.
The Sr. Director of Analytics will lead analytics initiatives, implement measurement strategies across digital media, websites, and apps, guide a team in data-driven insights, and optimize user experiences. Responsibilities include analytics strategy development, performance measurement, and business intelligence to enhance client marketing effectiveness and business growth.
As Sr. Director of Analytics at MERGE, you will lead analytics initiatives to enhance media and digital performance, guiding a team to implement analytics frameworks and drive insights. You will focus on conversion optimization and oversee tagging and tracking for accurate data collection, aiming to improve user experiences and business outcomes.
As a Machine Learning Engineer, you will develop and deploy machine learning models to tackle complex business problems. Responsibilities include collaborating with cross-functional teams, analyzing data, optimizing models, and ensuring production-quality deployments while staying updated on machine learning advancements.
As the Lead Machine Learning Engineer, you will develop and implement machine learning models for digital advertising performance, collaborate with software engineers, innovate ML solutions, mentor a growing team, and ensure models are effective and scalable.
Manager of Generative AI team responsible for managing and leading researchers and engineers. Leverage expertise in LLMs and generative models to create AI roadmap. Work on cutting-edge technologies and collaborate with professionals.
Lead a team of data scientists and engineers to develop innovative measurement products and data-driven solutions, ensure high-quality project delivery, and establish best practices for data science projects. Collaborate with multiple teams to enhance TV measurement and methodology while mentoring team members and advancing an inclusive culture.
The AI Senior Data Scientist will develop and deliver Generative AI solutions, collaborating with cross-functional teams. Key responsibilities include applying advanced AI techniques, ensuring high-quality data integrity, coaching junior members, and designing innovative solutions to complex business problems.
The MLOps Engineer will develop systems and APIs for inference and fine-tuning of large language models, implement runtime systems for production-level ML training, and collaborate with various teams for deploying and maintaining ML inference systems.
As an ML Engineer at Together AI, you will develop a platform for customizing open-source models, collaborate with product and research teams, ensure API reliability, and contribute to the open-source AI ecosystem. Key responsibilities include building systems, creating tooling, ensuring stability, analyzing methods, and developing new features. Ideal candidates have 2+ years of ML deployment experience, knowledge of fine-tuning methods, strong Python or Go skills, and a passion for reliable tools. Standout experiences include large-scale system development, advanced fine-tuning methods, open-source contribution, and ML workload management on Kubernetes.
The Machine Learning Engineer will optimize AI inference systems, develop runtime inference services, and collaborate with teams to enhance AI capabilities. Responsibilities include designing production systems, conducting code reviews, and implementing robust data processing systems.
Research and build the next generation AI platform at Together AI, design large-scale distributed training systems and low-latency/high-throughput inference engine, stay up-to-date with latest advancements in machine learning systems.
AI Researcher responsible for developing novel architectures, system optimizations, and algorithms to push the frontier of open models. Collaborate with cross-functional teams and stay updated on the latest advancements in machine learning. Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or related field required.
The Lead Data Scientist will build and mentor a team, define the technical vision, design advanced search algorithms, develop machine learning models to personalize user experiences, conduct data analysis, and collaborate with product teams to turn business needs into data projects.
As a Machine Learning Scientist, you will drive research in generative modeling technologies for biomolecular design, develop deep learning methods for protein prediction, curate datasets, and collaborate with biology teams. The role requires implementing and analyzing computational approaches and shaping the scientific vision of the company.
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