Top Machine Learning Jobs in Mexico City

Bridges business stakeholders, AI and data teams, and software engineers by identifying AI automation opportunities, documenting requirements, creating user stories, and supporting Agile delivery. Evaluates AI-generated outputs, defines success metrics, and contributes to change management, onboarding, training, and organization-wide AI adoption.

Lead enterprise delivery of Databricks-based data, analytics, and Generative AI solutions. Design production data pipelines, lakehouse architectures, RAG applications, ML platforms, and cloud-native systems. Drive legacy data migrations to Databricks, advise executive client stakeholders, identify platform expansion opportunities, and mentor engineering and consulting teams. The role combines hands-on engineering, solution architecture, customer engagement, and technical practice development.

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.

Leads Scribd’s content intelligence and UGC supply portfolio, owning corpus classification, metadata, quality, gap analysis, AI infrastructure, contributor experiences, and content acquisition strategy. Partners with ML, engineering, data science, consumer product, and business development teams to connect content supply with business value. Manages senior product leaders and established engineering and analytics programs while setting portfolio roadmaps and representing content strategy with executives.

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.

Leads the plant’s automation, controls, robotics, and digitalization portfolio for blade manufacturing. Responsibilities include designing and specifying automated systems, programming robotic and PLC-based controls, modeling solutions, managing suppliers, executing validation and commissioning, completing safety assessments, and handing systems over to Production and Maintenance. The role establishes technical standards, applies manufacturing readiness frameworks, uses analytics, SPC, and AI-based process monitoring, manages capital projects, mentors technical teams, and supports continuous improvement and operational excellence.

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.

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.

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 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.

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 high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

Analyze operational workflows to identify automation opportunities; design, build, test, and maintain automated workflows and AI-enabled solutions; partner with stakeholders to gather requirements; document processes; monitor and optimize automation performance; support change management, training, and reporting on efficiency and quality improvements.

Own and set technical direction for the Everand backend, building scalable, reliable systems for discoverability, personalization, and core consumption journeys. Drive architecture, platform health (CI/CD, staging, DBs, queues, cost, observability), mentor engineers, lead cross-team planning, modernize legacy systems, and partner with product, design, analytics, web/mobile, and ML to support experimentation and telemetry-driven decisions.

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.

Work with the data science team to understand insurance data and fraud, build and optimize mathematical models and algorithms, implement production-quality code, participate in client workshops to gather feedback, and propose continuous improvements.

The CX Tools & Automation Analyst will automate customer support tickets using APIs, optimize authentication methods, and enhance tooling efficiency while collaborating with stakeholders and documenting changes.

Owns AI and machine learning model and agent behavior from problem framing and algorithm selection through fine-tuning, retrieval, orchestration, evaluation, and production serving. The role requires deep expertise in machine learning, neural networks, statistics, agent memory, knowledge graphs, cloud deployment, and production model lifecycle tooling. Partners with data engineering while leading algorithm, prompting, and evaluation decisions, with opportunities to guide technical discovery and client workshops.

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 the architecture and development of scalable AI/ML pipelines and production systems, including LLMs and Generative AI. Mentor engineering teams, guide technical decisions, operationalize models, optimize performance and costs, and implement MLOps practices such as CI/CD, monitoring, versioning, and maintenance. Partner with executives, clients, product managers, data scientists, and software engineers to align AI roadmaps with business goals and integrate ethical AI capabilities into enterprise applications.

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

Lead Salesforce product initiatives for Channel and Enterprise sales: gather and document requirements, build roadmaps, define solutions, drive implementation, enable adoption, produce reports, and partner with sales, sales ops, IT and enablement to improve selling effectiveness and reduce CRM admin burden.

Lead the design, development, and production deployment of machine learning models and predictive analytics pipelines. Collaborate with engineering, product, analytics, and data teams to optimize cloud-based data solutions, automate workflows, and apply statistical modeling to business challenges. Mentor junior data scientists, establish MLOps best practices, and communicate insights and recommendations to stakeholders and executives.