Top Machine Learning Jobs in Leon

Operate AI-assisted identity migration and demonstration pipelines, review and validate LLM-generated analyses and configurations, and remediate SailPoint Identity Security Cloud environments. Troubleshoot pipeline and product issues, create sales-ready deliverables, support proof-of-value engagements, and improve agentic tools, prompts, playbooks, and evaluation processes. Collaborate with sales, solution engineering, product, professional services, customer success, and forward-deployed engineering teams.

Leads plant-wide cost-reduction and continuous-improvement projects using Six Sigma, Lean Manufacturing, data analysis, machine learning, additive manufacturing, and Ford Production System practices. Responsibilities include DMAIC projects, root-cause analysis, predictive modeling, reporting automation, KPI tracking, process improvement, and cross-functional collaboration across manufacturing areas. The role is hands-on, on-site, and designed for early-career engineering talent.

Develop, train, evaluate, and optimize ML solutions and data pipelines; translate business requirements into production-ready ML code; perform feature engineering, model selection, and evaluation; document work, participate in code reviews, and support testing and data issue resolution.

Business Analyst supporting enterprise loyalty SaaS implementations for global brands. Responsibilities include client discovery, requirements analysis, KPI definition, business case development, loyalty strategy, platform configuration, implementation coordination, support, training, documentation, and stakeholder communication. The role also contributes to product innovation, marketing collateral, and go-to-market strategy. Candidates need up to three years of client delivery or enterprise SaaS implementation experience, strong analytical and communication skills, and fluency in English, Portuguese, and Spanish.

Analyzes human-generated data quality across AI programs using SQL, Python, statistical methods, and hands-on annotation review. Investigates quality issues, identifies failure patterns, measures impact, and develops recommendations. Supports quality pipelines, automated validations, rubrics, gold sets, calibration exercises, reporting, and dashboards. Collaborates with quality engineering, operations, delivery, and engineering teams to improve annotation design, training, tooling, and quality controls.

Analyzes veterinary and customer data to support hospital site selection, acquisitions, revenue optimization, forecasting, pricing, predictive modeling, and executive decision-making. Builds integrated datasets, statistical models, experiments, and interactive BI dashboards using SQL, Python or R, and visualization platforms. Communicates quantitative insights and recommendations to technical and business stakeholders.

Own complex AI and data projects from customer discussions through delivery, translating needs into execution plans and coordinating large networks of domain experts. Lead and develop project associates, manage customer relationships, analyze performance data, improve quality and efficiency, and identify expansion opportunities. Collaborate with Operations, Engineering, and Machine Learning teams while overseeing projects with substantial revenue and contributor scale.

Execute large-scale projects for AI labs and technology companies, managing expert networks, multimillion-dollar portfolios, delivery quality, operational issues, customer communication, and process improvements. The role requires analytical problem-solving, prioritization, ownership, and comfort with ambiguity while collaborating across operations, engineering, and machine learning teams. Candidates may be recent graduates and will work remotely from Mexico City before transitioning to an in-person model.

Lead and expand a strategic financial-institution account by developing executive relationships, structuring complex multi-million-dollar SaaS deals, creating joint business plans, and achieving sales targets. Collaborate with sales, product, delivery, and marketing teams to tailor enterprise solutions, advocate for client needs, and position FICO as a trusted analytics and decisioning partner. The role requires banking and financial-market expertise, resilience, consultative selling, and travel up to 50%.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Own end-to-end delivery of complex AI client projects, translating evolving requirements into project scopes, delivery plans, and successful human data programs. Manage client relationships, cross-functional coordination, risks, quality, timelines, budgets, profitability, and delivery metrics. Partner with Sales, Operations, Product, and Engineering while improving scalable processes for AI project execution.

Lead commercial, privacy, and product legal functions for a cloud technology company. Draft and negotiate enterprise SaaS, partnership, reseller, and other technology agreements; advise on global privacy, data protection, AI, intellectual property, and product development; build legal playbooks and scalable contracting processes; and partner with Sales, Product, Engineering, Security, Compliance, and executive teams. Manage, mentor, and develop legal professionals while overseeing complex transactions and regulatory risk.

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.

Designs, develops, integrates, and deploys intelligent solutions using machine learning, deep learning, generative AI, and LLMs. Builds production-ready AI applications, RAG pipelines, and NLP systems; manages model evaluation, optimization, monitoring, versioning, and deployment. Collaborates with engineering, product, and data teams in a distributed environment while emphasizing scalability, maintainability, testing, observability, responsible AI, and cost efficiency.

Build end-to-end products from frontend React UIs to backend Python/FastAPI APIs. Develop and productionize Python-based ML/NLP pipelines and model inference APIs. Manage data processing workflows, containerization (Docker/ECS/Fargate), CI/CD, and cloud deployments (AWS or cloud-agnostic). Collaborate in agile teams and focus on scalable architecture and ML productionization.

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.

Lead strategic enterprise sales for a major financial client: build C-suite relationships, design tailored SaaS analytics solutions, negotiate complex multi-million-dollar deals, advocate client needs internally, drive account expansion and meet quarterly/annual sales targets. Requires collaboration across sales, product, delivery, and marketing and travel up to 50%.

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.

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.

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.