Top Machine Learning Jobs in Leon

Lead the Discover engineering team to develop a recommendation engine for a new marketplace, focusing on machine learning systems and user experience.

The role involves building a recommendation engine, designing ML systems, making data-driven decisions, and collaborating with leadership to enhance user experiences.

Own and drive the identity product strategy and roadmap for onboarding, verification, authentication, and account recovery. Collaborate with engineering, design, fraud, and compliance to build secure, scalable identity systems, design data schemas, define KPIs, and explore AI/ML solutions to improve verification and user experience.

The Data & Automation Lead will oversee data cleansing, ingestion, and automation, collaborating with product and engineering teams to ensure data reliability and effectiveness in product features.

The AI Transformation Lead will drive AI delivery capabilities, transforming internal operations and client programs, while embedding AI practices and managing teams to ensure successful implementation and measurable outcomes.

The Solutions Consultant will engage with customers to deploy Snowflake solutions, enhance internal tooling, and deliver outcomes for modernization projects.

As a Senior Software Engineer, you'll design and maintain API solutions, collaborate with cross-functional teams, and ensure software quality through testing and documentation.

Join Imubit as a Control System Engineer, integrating AI with DCS for process control in industrial settings. Collaborate on projects and improve system performance, requiring 5+ years of experience.

The Principal, Strategic Accounts & Insights is responsible for managing high-value client relationships, driving commercial growth, and aligning business strategies with technical delivery, requiring both strategic ownership and data expertise.

The Data Analytics Business Partner will bridge advanced analytics with business leadership, developing predictive models and data solutions to enhance customer engagement and optimize performance across LATAM markets.

Lead the design, development, and maintenance of AI/ML solutions while ensuring adherence to agile best practices, collaborating with stakeholders, and implementing security measures.

The AI/ML Director will lead the development of AI solutions, overseeing technical design, architecture, and project implementation while fostering an agile and quality-first environment.

The ML/AI Associate Director will lead the Foreseer AI team, overseeing platform development and technical design, while fostering an agile culture. Responsibilities include collaboration with stakeholders, compliance, and documentation.

The ML Engineer will productionize machine learning models, enforce engineering standards, collaborate with Data Scientists and Engineers, and mentor junior staff.

The role involves designing and implementing GenAI and MLOps solutions, developing production-ready ML code, and collaborating with Data Science teams to integrate AI models. It demands hands-on experience in data processing, cloud architectures, and AI concepts.

Design, build, and deploy machine learning models for data-driven products. Collaborate with teams, optimize pipelines, and maintain model performance.

As a Senior Machine Learning Engineer, you will collaborate on LLM applications, focusing on scalability, API integration, and data management for production-quality systems.

Seeking a Machine Learning Architect to lead AWS solutions by designing ML systems, mentoring peers, and managing project deliverables. Responsibilities include backlog management, troubleshooting, automating tests, and ensuring client satisfaction.

The Data Scientist - ML Engineering will architect ML infrastructure, lead ML solutions deployment, manage CI/CD workflows, and mentor MLOps engineers.

Develop and implement machine learning models to optimize financial processes, enhance existing models, and collaborate on integrating solutions into company systems.

Lead design, development, and deployment of production ML models. Work with large datasets to build predictive pipelines, collaborate with data engineers on cloud architectures, automate MLOps/CI-CD, mentor junior staff, and communicate insights to stakeholders to inform business decisions.