Top Machine Learning Jobs in Mexico

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

The intern will collaborate with Data Engineering and Data Science teams to build data pipelines, develop analytics solutions, and support AI/ML model development for engineering applications.

The Senior Tools & Metrics Manager will develop and maintain the tooling ecosystem for Operations, ensure effective data management, and collaborate with technical teams to enhance reporting and workflows.

The Key Account Manager oversees operations, manages strategic partnerships, optimizes sales, and leads a sales team, aiming for account growth and performance.

The Partner Success Operations Analyst ensures efficient merchant operations through process optimization, portfolio management, and communication with partners, while also providing insights for continuous improvement and risk management.

Oversee and expand technical professional services and consulting, driving development and quality of services while building relationships with executive clients to support their digital transformation.

The HR AI Specialist designs and deploys AI and ML models to optimize HR workflows, ensuring compliance and integrating with IT systems.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, collaborate on machine learning models, and support analytics initiatives for various business teams.

Lead and optimize PayJoy's global fraud operations, managing a team to prevent fraud across consumer and SME products while driving strategic initiatives and operational improvements.

Lead architecture and delivery of production-grade ML solutions for industrial IoT: predictive maintenance, anomaly detection, time-series forecasting, and real-time edge/cloud inference. Build robust data pipelines, mentor engineers, enforce ML best practices, and align technical roadmaps with business outcomes.

Design, train, and refine machine learning algorithms on high-dimensional data to produce practical predictive models. Apply random forests, deep learning, generative modeling, and neural-network techniques to improve NLP and machine perception for real-world applications.

Lead design and implementation of agentic AI/ML solutions and modern software (APIs, microservices, CI/CD, streaming) on cloud platforms. Bridge legacy IBMi AS400 systems with modern AI, train and fine-tune models, oversee lifecycle, mentor engineers, set technical direction, and improve automation and testing across claims adjudication systems.

The Staff Software Development Engineer will lead software development projects, implement AI/ML solutions, oversee system architecture, and mentor teams, focusing on both legacy and modern technologies.

Design, develop, and deploy large-scale machine learning models; perform data analysis, feature engineering, and model optimization; collaborate with data scientists and engineers to productionize solutions using AWS and distributed frameworks.

As a Senior Machine Learning Engineer, you will develop and maintain infrastructure for ML applications, collaborate across teams, and drive tool development for data processing and model deployment.

The Senior Data Scientist will develop AI algorithms, optimize building operations, generate insights, and collaborate with teams to implement solutions.

Build and own production ML and LLM systems for onboarding, risk, compliance, and operations. Design models, engineer features from messy data, balance performance and interpretability, integrate with backend training/inference pipelines, write tested code, and partner with product and operations to drive scalable, reliable automation.

Lead the design, development, and deployment of machine learning and deep learning systems. Own the lifecycle of ML models including deployment, monitoring, and retraining. Collaborate with other technical teams and mentor staff. Research emerging techniques and improve operational efficiency.

Build and maintain Azure-focused ML/LLM infrastructure and CI/CD pipelines using Terraform and Azure DevOps; operationalize LLM inference, retraining, RAG pipelines, and monitoring; ensure security, scalability, and collaboration with data scientists and product teams to deliver production AI features.

Build and operate scalable, secure ML/LLM infrastructure on Azure using Terraform and Azure DevOps. Implement end-to-end ML pipelines, manage model lifecycle, deploy inference services (AKS/Functions), integrate vector DBs and orchestration tools, and collaborate with data science and product teams to productionize generative AI features.

Build and maintain ML pipelines, implement CI/CD for models, deploy and integrate models into APIs/services, monitor performance and drift, manage model versioning, and collaborate with Data Science and Data Engineering teams to deliver scalable production ML solutions.

The intern will develop AI models, enhance neural mechanism understanding, and collaborate on generative modeling while maintaining code quality.

The Data Scientist will develop machine learning models, apply optimization techniques, analyze complex datasets, and collaborate with cross-functional teams to deliver solutions tailored to life sciences and related industries.

The Machine Learning Analyst collaborates with AI/ML teams to identify data requirements, implements data ingestion pipelines, and ensures data quality while supporting data scientists in model development.

The Sr AI/ML Engineer will design and deploy machine learning models, build computer vision systems, and develop LLM-based features in a collaborative, fast-paced environment.