Top Machine Learning Jobs in Mexico City

The Machine Learning Researcher will design datasets and evaluate environments for agentic systems, focusing on data quality and benchmarking model performance in RL settings. They will collaborate with teams to translate workflows into evaluative frameworks and improve the understanding of high-quality datasets.

Analyze large federal and state economic datasets, automate data collection and scraping, and rapidly publish clear, data-driven reporting on market-moving indicators. Collaborate with reporters and visual journalists, file public-records requests, and use emerging technologies including AI to enhance real-time coverage.

Design, implement, and scale event-driven, distributed backend systems in Python on AWS to process and enrich large-scale document and media datasets. Lead technical projects, mentor engineers, integrate ML/LLM components, optimize performance, maintain observability, and collaborate with Data Science, ML Engineering, and Product to deliver reliable high-throughput content processing services.

Lead full presales cycle for cloud, data, and AI deals; design AWS-based solutions; manage pipeline in Salesforce; engage CTOs and execs; develop GTM assets; mentor and grow a high-performing team; drive US cultural and technical process adoption across regional branches.

Lead end-to-end supply chain transformation engagements for commercial and utility clients. Advise executives, design future-state supply chain architectures, oversee implementation across planning, procurement, logistics, and analytics, build financial value cases, and manage multidisciplinary teams to deliver measurable operational and financial results.

Lead end-to-end supply chain transformation engagements, advising executives and directing multidisciplinary teams to improve planning, procurement, logistics, inventory, and supplier performance. Design future-state architectures, build business cases, drive implementation, grow client relationships, and scale practice capabilities while delivering measurable operational and financial impact.

The Director of Research will lead DataLab at Protege, defining the research agenda and managing a high-performing team focused on AI data challenges and methodologies.

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

Lead statistical activities for clinical trials from protocol design through reporting. Provide statistical oversight, collaborate with cross-functional teams and CROs, apply SAS/R (and ML) for analyses, automate processes, and mentor junior statisticians.

Design, build, deploy and monitor ML models for fraud detection, credit risk, churn, cross-sell and collections. Handle large datasets, feature engineering, production-grade code, and scalable feature/model pipelines. Collaborate with risk, fraud, engineering and product teams and integrate new data sources to improve model performance in international markets.

Develop, deploy, and monitor production ML models and infrastructure for fraud detection across global markets. Own feature engineering, model lifecycle, scalable pipelines, and collaborate with fraud, product, engineering, and risk teams to improve model performance and decisioning.

This role involves leading strategic planning, product innovation, and cross-functional collaboration to enhance pharmacy analytics and drive growth initiatives for CVS Health.

Create and review realistic, locale-specific robotics and natural sciences tasks in Spanish (LATAM), apply scoring rubrics, evaluate AI and human responses for accuracy and regulatory alignment, and produce gold-standard solutions and expert feedback.

Design, build, and maintain production-grade ML systems for large-scale legal NLP datasets. Develop and orchestrate ML/AI agents, prototype solutions, collaborate with cross-functional teams, and work with legal data annotators to improve data quality and drive product-focused outcomes.

As an AI/ML Engineer, design and implement AI solutions, collaborate with teams, build ML pipelines, and ensure quality and compliance in healthcare applications.

Design, build, and maintain scalable data pipelines, vector stores, feature stores, and LLM-driven workflows. Implement RAG, prompt engineering, model fine-tuning, and managed LLM deployments on cloud. Optimize big-data processing, enable real-time inference, build analytics/NL query dashboards, document processes, and partner with stakeholders to translate requirements into production BI/ML solutions.

Develop and validate change-detection and anomaly models on multi-temporal Sentinel imagery for pipeline corridors. Fine-tune geospatial foundation models with LoRA/PEFT, implement SAR displacement methods and dune-migration tracking, engineer data ingestion from Copernicus/STAC sources, design labelling and validation strategies, and communicate results to technical and business stakeholders.

The role involves developing and maintaining a robust ML/AI platform, focusing on infrastructure, autonomous agents, CI/CD pipelines, and AI-native tooling, with responsibilities across engineering best practices.

The Account Executive will develop and close business opportunities, achieve sales quotas, and collaborate with cross-functional teams within the enterprise market.

Develop and calibrate change-detection and anomaly models on multi-temporal Sentinel-1/2 imagery to detect sand encroachment and pipeline displacement. Fine-tune geospatial foundation models, implement SAR displacement techniques, build dune-migration tracking, engineer Copernicus data ingestion, design labeling and validation strategy, and communicate results to stakeholders.

Design, architect, and deliver enterprise-grade generative AI solutions (LLMs) for healthcare. Build end-to-end ML pipelines, scalable cloud deployments, APIs and integrations, prompt engineering, RAG and conversational systems. Ensure responsible AI, privacy compliance, performance optimization, and cross-functional collaboration while documenting architectures and best practices.

Lead technical client engagements in machine learning and AI, shape strategy, influence architecture, and ensure high-quality outcomes for clients by leveraging AWS services.

Lead a team of ML engineers, manage client engagements, and provide strategic advisory on ML architecture while driving pre-sales. Ensure team growth and quality of deliverables.

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

The Senior Machine Learning Engineer will build and optimize ML systems for CRM marketing, collaborating with cross-functional teams to impact customer engagement and product functionality.