Top Machine Learning Jobs in Leon

Analyze production drive-thru voice AI data, build SQL reports and dashboards, monitor KPIs, identify conversation error patterns, and improve NLU models, conversation flows, and LLM behavior through machine learning and rule-based techniques.

Supervise a customer support team by managing daily operations, escalations, coaching, performance reviews, training, attendance, and KPI achievement. Coordinate with internal managers and HR, ensure equipment and service needs are met, and communicate with clients regarding complex requests, complaints, processes, and continuous improvement. The role also supports team development, culture building, and customer service quality.

Develops and maintains statistical, econometric, optimization, and machine learning models supporting Nielsen’s PPM audience measurement production processes. Responsibilities include building data pipelines, querying large datasets, performing analyses and visualizations, managing sampling algorithms, implementing quality checks, and delivering data-driven recommendations. The role also contributes to software development, testing, code reviews, CI/CD practices, documentation, cross-functional projects, and client requests.

Reviews real-time transactions and customer behavior flagged for fraud, investigates cases using internal policies and data analysis, and determines whether activity is fraudulent. The intern helps identify emerging fraud trends, improve detection rules and machine learning models, maintain case-resolution SLAs, and handle escalations. The role collaborates with analysts, operations specialists, data scientists, engineers, and support teams while contributing to fraud-prevention processes and tools.

Reviews real-time transactions and customer behavior for fraud and abuse, investigates suspicious activity, blocks risky users, clears false positives, and handles escalations. The analyst identifies fraud trends, analyzes account patterns, supports machine learning and detection improvements, collaborates with cross-functional teams, maintains fraud expertise, and meets case-resolution SLAs.

Leads data engineering, Palantir Skywise architecture, and AI solution development for Airbus manufacturing and operational environments. Builds scalable pipelines, analytical workflows, machine learning and generative AI applications, and enterprise data foundations. Oversees Alteryx and Tableau platforms, establishes governance, mentors technical teams, translates business challenges into data products, and supports AI Center of Excellence initiatives. The role is onsite 60% across several U.S. locations and requires approximately 10% travel.

Conduct offensive, AI-driven red-team assessments by validating automated attacker decisions, resolving authentication and CAPTCHA challenges, guiding reconnaissance, classifying attack data, and providing feedback to improve security models. The role requires maintaining context across multiple client engagements, making safety-critical judgments, and documenting technical decisions. Candidates need at least one year of relevant experience through work, internships, classes, or projects, plus authorization to work in Mexico without sponsorship.

Leads the build-out and operation of XDOF’s LATAM robotics data-collection network in Mexico or Brazil. Responsibilities include expanding collection venues, sourcing partnerships, recruiting and managing field teams, deploying and maintaining hardware, optimizing operational efficiency, monitoring data quality, and converting market learnings into reusable SOPs and playbooks.

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.

Mercor is offering $5 million in grants for independent researchers, academics, PhD students, and small teams conducting frontier AI safety research. Focus areas include misalignment, sandbox escape, evaluation awareness, interpretability, oversight and control, and red-teaming. Funding may support researcher time, API credits, and conference attendance. Applicants should submit a focused expression of interest describing their team, background, research proposal, outputs, impact, timelines, and resource needs.

Own and improve the Command|Alert alerting platform, including rule evaluation, anomaly detection, event correlation, reliable Kafka and OpenSearch pipelines, and downstream notifications. Convert security and network telemetry into usable topologies and dependency maps, support LLM-based alert generation, resolve production issues, lead reliability improvements, deliver independent projects, and mentor engineers while shaping technical direction.

Designs and maintains Coveo data ingestion and indexing pipelines, integrating enterprise data sources and configuring metadata, schemas, mappings, and enrichment. Optimizes search relevance using query pipelines, ranking strategies, and machine learning. Monitors analytics and platform performance, troubleshoots synchronization issues, supports data governance, and contributes to AI Search, Generative AI, and knowledge management initiatives. Partners with engineering, product, and business teams to improve enterprise information access.

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.

Build and operate production machine learning and data pipelines on Databricks. Responsibilities include orchestrating Jobs workflows, managing Databricks Asset Bundle deployments across environments and countries, administering MLflow and Unity Catalog model lifecycles, monitoring compute costs and observability, and diagnosing runtime incidents. The role requires advanced Python, SQL, Delta, Unity Catalog, CI/CD, Azure DevOps, Git, infrastructure as code, and Databricks platform expertise.

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.

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.

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 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.