Top Machine Learning Jobs in Mexico

Designs and optimizes Retrieval-Augmented Generation systems, including document ingestion, chunking, embeddings, retrieval, reranking, vector search, and source-grounded responses. Develops evaluation frameworks to measure relevance, citation accuracy, factual grounding, latency, cost, and hallucination reduction. Collaborates cross-functionally to deliver scalable, trustworthy, and responsible Generative AI solutions for legal and professional information products. Preferred work includes AI agents, LLM workflows, hybrid search, observability, and regulated-domain applications.

Develop experimental AI techniques for agentic marketing applications, especially image and video generation. Build proofs of concept, autonomous evaluation and improvement systems, realistic AI-generated video, and brand-aligned creative generation workflows. The role requires strong quantitative and probabilistic thinking, backend architecture skills, creativity with LLM applications, and product intuition.

Lead a team of full-stack product and data engineers building personalized, high-converting checkout experiences. Drive experimentation, ML-powered optimization, data platform development, technical architecture, roadmap planning, incident response, cross-functional delivery, talent recruitment, and engineering team mentorship.

Leads product growth and digital insights for a business application, owning local product strategy, roadmap prioritization, discovery, requirements, and stakeholder alignment. Manages an AI and machine learning personalization squad developing recommendation, cross-sell, and upsell models. Owns data management, analytics, experimentation, impact measurement, and business insights to support data-driven decisions. The role bridges business, technology, and data teams across regional environments.

Leads the Advanced Manufacturing Engineering team and molding technology strategy for composite blade manufacturing. Directs process development, testing, validation, industrialization, automation, data analysis, technology roadmaps, supplier performance, and capital planning. Oversees molding processes including mold preparation, gel coat, fiber layup, resin infusion, curing, and bonding. Develops engineers, manages project portfolios, ensures technical documentation and change control, and drives safety, quality, cost, productivity, and operational excellence improvements.

Develop product positioning, messaging, content, and go-to-market assets for an AI training data platform. Lead end-to-end product, vertical, DataLab, and commercial launches; translate complex AI and data concepts for technical buyers; create thought leadership, case studies, decks, webinars, videos, social content, and landing pages; and partner with Product, Sales, DataLab, Community, and business leaders to strengthen market narrative and support commercial growth.

Lead the strategic roadmap and business integration of CVS Health’s Clinical Insights Engine across screening, diagnosis, quality measurement, or care management use cases. Partner with platform product managers, clinical leaders, business owners, and technology teams to align clinical needs with scalable platform capabilities. Drive adoption, value realization, KPI monitoring, business cases, and continuous product improvement while ensuring measurable clinical and financial outcomes.

Lead customer success for an energy-sector client portfolio by developing adoption and success strategies, serving as a trusted advisor, and delivering analytics solutions using Spotfire. Apply machine learning, statistical modeling, optimization, AI, large language models, digital twins, and anomaly detection to customer problems. Collaborate with sales, support, product, and engineering; guide prototypes and R&D; provide demonstrations, training, thought leadership, and industry presentations. Coach colleagues and operate with limited oversight.

Owns the design, development, deployment, and support of Snowflake data models, Streamlit applications, BI reports, and AI-powered data products. Integrates machine learning models, RAG endpoints, and agentic LLM services into reliable user-facing tools. Partners with data scientists, engineers, and go-to-market stakeholders to translate business needs into trustworthy analytics solutions for a B2B SaaS organization.

Conduct machine learning research, develop AI and ML product feature prototypes, and solve business problems using structured and unstructured data. Collaborate with product, engineering, sales, and customer success teams to define data science initiatives. Apply statistical methods, NLP, classic machine learning, and agentic AI. Manage complex projects, translate research into actionable insights, and communicate technical concepts to stakeholders.

Own AI and machine learning research projects that improve sales productivity. Apply agentic systems, NLP, and machine learning; design experiments; develop prototypes and production-ready models; collaborate with product, design, and engineering; influence the AI roadmap; and mentor junior researchers.

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.

Develop and maintain customer-facing Tableau reports, collaborate with customer service and development teams to scope and model data, ensure data accuracy, analyze complex datasets, and communicate actionable insights to stakeholders.

Develop integrated software algorithms and data-driven monitoring/analytics systems. Work with large-scale computing frameworks, apply machine learning and statistical modeling, translate customer requirements into solutions, document installation/maintenance procedures, and solve complex problems with a security-first mindset.

Leads data science strategy across Mexico and Brazil, manages and mentors a distributed team, and remains hands-on building and deploying machine learning models. Establishes modeling standards, infrastructure, delivery practices, and technical roadmaps while partnering with credit leadership on underwriting, valuation, impact measurement, and P&L analysis. Requires strong applied machine learning expertise, prior data science leadership, business communication skills, and understanding of credit or underwriting.

Leads enterprise sales strategy and revenue growth for AI-powered eDiscovery, legal technology, compliance, analytics, and data intelligence solutions. Builds pipelines, manages complex consultative sales cycles, develops executive client relationships, expands strategic accounts, and positions responsible AI adoption. Partners with product, operations, legal, security, marketing, and executive teams on solution development, pricing, contracts, implementation, and market expansion across corporations, law firms, government, and regulated industries.

Lead XPENG Mexico’s public relations and communications strategy, including media relations, influencer partnerships, crisis management, product launches, experiential PR, technology storytelling, executive thought leadership, and agency oversight. Build the company’s reputation as an AI mobility and technology leader while coordinating with Sales, Product, PR, and global headquarters. Manage influencer budgets, measure campaign ROI, and translate complex AI and EV innovations into compelling local narratives.

Develop and operationalize AI and analytics solutions using Palantir Foundry, machine learning, data modeling, data mining, and visualization. Partner with Finance and Lead Gen stakeholders to translate business needs into scalable workflows, validate results, improve data quality, and measure model performance. Document model logic and implementation details while collaborating across technical and business teams.

Designs, analyzes, optimizes, and benchmarks quantum algorithms across cryptography, chemistry, finance, materials science, and defense. Performs resource estimation for near-term and fault-tolerant hardware, develops compilation and error-mitigation techniques, translates customer problems into quantum tasks, and supports proof-of-concept engagements, publications, government deliverables, and product improvements. The role requires independent scientific analysis and collaboration with software engineers and domain experts.

Lead technical strategy and execution for production clinical AI across a portfolio: set AI direction, ensure regulatory and governance alignment, partner with product and engineering, improve model evaluation/monitoring and production reliability/cost/latency, promote reusable model patterns, and hire/coach data science leaders to scale clinical AI capabilities.

Act as liaison between clients and project teams to elicit business requirements, convert them into data-driven and AI use cases, coordinate data architecture, modeling, engineering and science efforts, facilitate agile ceremonies, support testing and UAT, monitor project progress, and document user manuals and training materials.

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.

Support development and validation of forecasting, optimization, clustering, anomaly detection, and generative AI models. Prepare and analyze data, assist with model monitoring and retraining, and collaborate with senior data scientists on live enterprise deployments while learning production best practices.

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.

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.