Top Machine Learning Jobs in Mexico

Perform part-time remote data tasks to improve Spanish (Mexico) AI outputs: collect, evaluate, annotate, and tag content across audio, video, images, and other data; perform pairwise comparisons and counting tasks. Flexible schedule, immediate start.

As a Data Scientist at Zicasso, you will analyze complex datasets, develop predictive models, and optimize customer experiences using AI and machine learning techniques, while collaborating with cross-functional teams.

The Senior Data Analyst will interpret ML/AI model outputs, create executive reports, write SQL and Python scripts for data analysis, and develop dashboards to monitor business KPIs. They will also ensure data governance and communicate insights to senior executives.

Drive advanced manufacturing strategies and optimize processes while implementing technologies for operational excellence and innovation. Collaborate with teams to improve productivity and lead various engineering tasks, also focusing on automation and robotics.

Lead high-impact customer pipelines for Scale's Generative AI unit: design data taxonomies, build pipeline infrastructure, manage global teams, create analytics, partner with Engineering/Product/Ops/Go-to-Market, and report to executives to drive multi-million dollar revenue growth.

Internship position focused on building ML-powered products. Responsibilities include software data analysis, product development support, and gaining proficiency in machine learning and SQL.

The Lead Metallurgist will oversee mineral resource evaluation, ensure quality control, audit geometallurgical models, and provide technical leadership, focusing on optimizing mine operations through advanced modeling and collaboration with teams.

Lead the design, development, and delivery of AI solutions, ensuring high-quality engineering practices and mentoring team members in AI/ML development.

Lead design, development, and delivery of AI solutions, ensuring code quality and scalability. Mentor team members and contribute to technical leadership.

The role involves leading AI architecture, designing scalable AI solutions, implementing Generative and Agentic AI, and mentoring teams.

Lead the design and deployment of AI systems, driving enterprise-scale solutions while mentoring engineers and shaping AI strategy.

The Senior Public Relations Manager will lead global PR strategy, manage media relations, develop storytelling, and handle reputation management for PayJoy.

The Digital Solution Executive will drive sales of digital solutions, design proposals, and manage complex deal logistics and negotiations.

The Salesforce Developer will design scalable solutions, write code using Apex and LWC, leverage AI for productivity, and ensure application performance while collaborating with various stakeholders.

The Staff Threat Researcher and Intelligence Engineer leads advanced research on cyber threats, architects scalable intelligence workflows, and mentors team members while collaborating with various stakeholders.

Lead data science initiatives for Growth and Go-to-Market: design experimentation and causal analyses, build forecasting and recommendation systems, advise stakeholders, set team strategy, and mentor data scientists.

The Director will manage program execution, improve processes, identify risks, collaborate with leadership, and ensure quality and budget compliance across teams.

The Data & Automation Lead will oversee data cleansing, ingestion, and automation, collaborating with product and engineering teams to ensure data reliability and effectiveness in product features.

Manage a team of cloud engineers and architects, oversee data delivery engagements, handle technical responsibilities, and interface with clients for technical improvements.

The Promoter Agencies Manager will oversee field marketing agencies to drive customer engagement and sales through a national demand generation strategy. Responsibilities include managing agency relationships, analyzing marketing metrics, and coordinating marketing initiatives.

The role involves designing, developing, and deploying AI/ML solutions focusing on Retrieval-Augmented Generation. The engineer will optimize retrieval performance, build data pipelines, and collaborate within teams while staying updated on AI advancements.

The Solutions Consultant will engage with customers to deploy Snowflake solutions, enhance internal tooling, and deliver outcomes for modernization projects.

Lead cloud architecture design and propagate architecture standards. Design, migrate and maintain cloud/serverless solutions on Azure, ensure nonfunctional requirements, support project and application managers, and communicate architecture to development teams.

The ML Engineer will design, build, and operationalize AI systems for unstructured data, developing ML pipelines and collaborating with Data Scientists and Engineers to deliver scalable AI solutions.

Design and implement scalable Generative AI architectures, build Python services, integrate LLMs, oversee deployment operations, and evaluate emerging technologies.