Top Machine Learning Jobs in Mexico
The Applied AI/ML Lead will analyze business problems and develop machine learning solutions, collaborating with various teams to implement AI/ML initiatives. Responsibilities include leading projects, creating models for NLP and recommendations, and deploying solutions into production while ensuring effective communication with stakeholders.
As a Senior Product Delivery Associate in Machine Learning Operations Intelligence, you will manage product delivery, support change initiatives, and collaborate with cross-functional teams to enhance efficiencies and ensure compliance. Your role involves communication with stakeholders, managing product roadmaps, and continuously improving agile practices.
The Data Owner Director will strategize and deliver product data to support business operations and advanced analytics. Responsibilities include driving data quality, collaborating with stakeholders to understand data usage, prioritizing data issue resolution, managing data risks, and overseeing data-related initiatives while ensuring compliance with company standards.
The Applied AI Modeling Lead will drive the development of advanced analytical products, utilizing deep NLP knowledge to solve complex business problems. Responsibilities include delivering products, mentoring team members, and acting as a subject matter expert in machine learning and algorithms.
In this role, the Applied AI ML Senior Associate will develop models and systems for the bank's operations, applying NLP and machine learning expertise to solve complex business problems and generate insights. They will contribute to product development, act as a trusted advisor, and promote continuous learning within the organization.
As an Analytics Solutions Lead, you will spearhead complex machine learning projects across J.P. Morgan's operations. The role entails collaboration with engineers and data scientists to create and implement data-driven solutions that enhance client services and operational efficiency, while managing project teams and driving innovation.
As a Machine Learning Engineer at ZS, you will build and monitor model pipelines, scale algorithms for large datasets, enhance ML engineering platforms, implement ML Ops, and ensure high-quality deliverables. You will also conduct research on architecture patterns and collaborate with global teams to deliver projects efficiently.
As a Machine Learning Engineer at ZS, you will build and monitor model pipelines, scale ML algorithms, implement MLOps, and write production-ready code. You will ensure high quality deliverables, collaborate with client teams, and contribute to evaluating new technologies and architecture patterns.
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As a Machine Learning Engineer at ZS, you will design and implement model pipelines, scale algorithms for large datasets, develop and maintain ML engineering platforms, and ensure high-quality code for production readiness. You will collaborate with teams, participate in scrum meetings, and contribute to research on new technologies while focusing on continuous model improvement.
As a Machine Learning Engineer at ZS, you'll build and monitor model pipelines, scale algorithms for massive data sets, implement ML Ops, and produce high-quality code. You will collaborate with global teams, participate in scrum calls, and contribute to researching new technologies.
Seeking a Vice President in Applied AI/ML to lead the development and implementation of AI/ML solutions for forecasting and analytical capabilities within the FP&A organization. Responsibilities include designing and implementing AI/ML solutions, collaborating with stakeholders, staying updated with data science advancements, and mentoring junior data scientists.
Design and develop machine learning systems, preprocess and engineer features, research and implement machine learning algorithms, support tools for machine learning experiments, transform data science prototypes into machine learning models, develop applications based on business requirements.
As a Summer Associate at the Machine Learning Center of Excellence, you will use advanced machine learning techniques in areas like NLP and reinforcement learning. Your role involves collaborating with mentors to solve business challenges and enhance organizational operations, requiring expertise in machine learning, deep learning, and statistical methods.
The role involves conducting research in computer vision and machine learning, providing innovative solutions to internal project teams, documenting findings in scientific papers, and contributing to intellectual property protections.
Develop state-of-the-art machine learning models for NLP, speech analytics, and recommendation systems. Collaborate with various teams to deploy solutions into production and drive successful outcomes. Stay updated on the latest advancements in NLP concepts and machine learning techniques.
As a Senior Internal Audit Associate, you'll conduct audits focusing on risk assessment, control identification, and continuous monitoring for the Chief Data & Analytics Office. This role involves evaluating control effectiveness, communicating findings, and driving efficiency in audit processes through technology. Collaboration with stakeholders and staying updated on industry developments are key responsibilities.
The Director of Architecture for AI/ML drives the adoption of machine learning technologies, collaborates with stakeholders to frame business problems, establishes data engineering processes, and provides technical leadership throughout the machine learning lifecycle, developing end-to-end AI/ML solutions.
As a Machine Learning Scientist - NLP, you will leverage machine learning and deep learning techniques to solve complex problems in natural language processing and more. You will collaborate with various teams to deploy solutions in production, research new methods, and develop scalable models for real-world applications.
Applied AI/ML Senior Associate role at JPMorgan Chase & Co. Responsibilities include developing AI/ML solutions, collaborating with teams, and advising on optimal solutions. Required qualifications include advanced degree in analytical field, experience in AI/ML, NLP, and strong coding skills in Python.
As a Staff Machine Learning Engineer in the Risk team at Cash App, you'll develop ML solutions to mitigate risk and fraud while collaborating cross-functionally with various teams. You'll utilize your expertise in machine learning algorithms and data analysis to enhance product lifecycle management.
As a Senior Machine Learning Engineer, you will leverage your expertise to develop analytical and machine learning solutions focused on mitigating risk and fraud for Cash App. You'll collaborate with cross-functional teams to balance financial loss, regulatory risks, and enhance customer experiences, deploying updates regularly based on data-driven insights.
As a Senior Machine Learning Engineer in Personalization, you'll design and manage distributed services and tools for machine learning applications, lead projects across engineering boundaries, and collaborate with various teams. Your role includes building recommendation and ranking systems while ensuring high code quality and providing mentorship to teammates.
Design, build, and maintain Machine Learning systems to flag fraudulent activities in real-time. Collaborate with global colleagues on challenging technical problems. Lead the conception and implementation of large-scale experiments to validate novel ideas. Apply latest theoretical advancements to enhance existing products and technologies. Conduct experiments across various computer science domains.
Apply sophisticated machine learning methods in the Time Series and Reinforcement Learning group at JPMorgan Chase. Develop scalable tools for real-world problems in finance and operations, collaborating with various lines of business. Lead projects from conception to deployment of production-level machine learning applications.
As Vice President in the Machine Learning Scientist - NLP team, responsible for applying advanced ML techniques to tasks like NLP, speech analytics, time series, and recommendation systems. Collaborate with various teams, drive firm-wide initiatives, develop ML models, and contribute to knowledge sharing community. PhD in a quantitative discipline with 3 years of industry experience or MS with 5 years. Strong background in NLP, deep learning, machine learning toolkits, big data, and scalable model training. Experience in designing experiments, intrinsically evaluating model performance, and effective communication.
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