Top Machine Learning Jobs in Ecatepec
Lead Credit and Data Science functions for international markets. Develop risk models, credit policies, and innovative products to enhance customer experience and business growth. Collaborate with teams to adapt strategies based on market-specific data and consumer behavior.
The Staff Data Scientist is responsible for developing and implementing machine learning models and analytics to drive business growth and improve customer financial situations. This role requires close collaboration with product, tech, and finance teams, and involves the entire model development process from conception to deployment, focusing on credit risk models to enhance approval rates and reduce loss rates.
As a Staff Data Scientist at Empower, you will develop risk models and credit policies to drive competitive underwriting practices. You will lead teams to analyze consumer behaviors and adapt solutions for the Latin American market, enhancing customer financial well-being. This role is pivotal for launching innovative financial products and requires tackling complex geographic challenges.
As a Senior Manager in Machine Learning Engineering, you will design, build, and optimize machine learning systems, collaborate with Agile teams, and lead projects focused on ML model implementation and deployment using various technologies. Your role includes model training, data pipeline construction, and ensuring adherence to best practices in machine learning and AI.
As a Data Scientist on Square's Payments Platform team, you'll leverage analytics, machine learning, and engineering to improve payment processes. Your role includes designing metrics, leading experiments, building ETL pipelines, and collaborating with cross-functional teams to optimize payment efficiency and drive data-driven decision making.
Join the Predict team to enhance Alloy's machine learning fraud capabilities by architecting scalable systems, collaborating with multiple teams, and developing machine learning algorithms. You'll ensure low latency and high availability by managing interfaces between systems and participating in feature generation and on-call rotations.
As a Senior Distributed Systems Engineer (Machine Learning), you will develop and maintain high-quality, scalable AI solutions and services for a Machine Learning Platform. You will collaborate with product and engineering stakeholders to understand requirements, minimize deployment risks, and integrate AI innovations into product development, ensuring the delivery of tangible business value.
In this role, you will develop AI/ML strategies to enhance customer support, lead the development of natural language processing systems, and collaborate with other teams to integrate ML capabilities into Canva's product offerings.
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As a Staff Machine Learning Engineer at Canva, you'll develop AI/ML strategies to enhance customer support, lead the creation of natural language understanding systems, and collaborate with teams to leverage ML capabilities while mentoring other engineers.
The Sr. Manager will lead R&D teams to develop driver behavior detection algorithms from smartphone sensor data for Arity. Responsibilities include setting a vision for machine learning applications, aligning with product and engineering teams, and managing diverse data science teams while ensuring successful model deployment and strategic development.
As a Senior Machine Learning Engineer at Atlassian, you will develop and implement advanced machine learning algorithms, collaborate with various teams to enhance AI functionalities across products, and guide junior engineers. Your role includes designing architectures, conducting model evaluations, and ensuring effective AI integration throughout the organization.
As a Senior Software Engineer on the ML Platform team at Upstart, you will build and maintain software applications enabling machine learning models, develop infrastructure for model training, support automation, and collaborate with data engineers and scientists to enhance deployment processes.
The Staff Machine Learning Engineer will lead projects within the Square Conversational AI team, focusing on building scalable machine learning solutions. Responsibilities include collaborating with business leaders, developing ML products, mentoring team members, and overseeing the entire ML lifecycle from data collection to production.
As a Senior Data Scientist at Spring Health, you will work with the Customer Experience team to build data products, analyze member mental health journeys, and provide actionable insights to enhance customer satisfaction and product value. Your role involves collaborating with internal teams and implementing AI/ML capabilities to improve mental health care solutions.
As an Applied AI/ML Lead, you will spearhead large AI/ML initiatives, collaborate with various teams to develop and implement machine learning models, especially for NLP and generative AI applications. You will manage the end-to-end machine learning pipeline and ensure the alignment of technical solutions with business needs, requiring strong communication and leadership skills.
As a Senior Machine Learning Engineer at Affirm, you will develop machine learning models for assessing creditworthiness, build training and monitoring systems, and collaborate with product and engineering teams. You'll implement data pipelines and drive innovations in credit decisioning with cutting-edge technologies.
As a Senior Software Engineer in the Central AI team, you will build and maintain core infrastructure to support machine learning engineers and data scientists. Your role involves solving complex infrastructure challenges, leading projects, and collaborating with other teams to ensure effective AI integration.
As a Senior Machine Learning Engineer, you will work on productionizing machine learning applications and systems at scale. You'll participate in the design and implementation of ML applications, collaborating with Product and Data Science teams, and focus on optimizing ML models, building data pipelines, and ensuring high performance and availability of solutions. You will leverage cloud technologies and follow best practices in responsible AI.
As a Staff Machine Learning Ops Engineer at Grubhub, you will architect and develop scalable MLOps pipelines, oversee monorepo management, implement monitoring frameworks, drive platform improvements, enhance engineering standards, and establish processes for data lineage and model management.
The Machine Learning Infra Engineer will bridge the gap between data science and production systems by optimizing models for runtime performance, designing scalable MLOps pipelines, and implementing monitoring frameworks. They will work closely with data scientists to improve workflows and ensure reliability across the system, while also developing data versioning and deployment strategies.
The Principal Machine Learning Engineer will drive the development and implementation of machine learning algorithms, collaborate with product and engineering teams, design architectures, conduct experiments, and guide emerging ML engineers, ensuring the effective integration of AI across Atlassian's products and services.
The Senior Principal Machine Learning Engineer will guide the development and deployment of advanced machine learning algorithms, collaborating closely with various teams to integrate AI functionalities across Atlassian products. Responsibilities include designing system and model architectures, conducting experiments, mentoring other ML engineers, and ensuring the effective use of AI in the product suite.
As a Machine Learning Engineer on the On-Device ML team, you will design and prototype new features, build and implement ML models, collaborate with product teams, and launch and monitor model deployments, all aimed at enhancing Grammarly's writing assistance capabilities on devices.
The Staff Machine Learning Engineer will lead the development of a marketing experimentation platform, working with cross-functional teams to design scalable ML products for optimization and ROI measurement. Responsibilities include system architecture, stakeholder collaboration, and improving ML engineering practices.
The Sr Machine Learning Engineer will develop and maintain algorithms for Hulu's recommendation system, using advanced machine learning methods. Responsibilities include feature engineering, optimizing data pipelines, and collaborating with product and data teams to enhance personalization and analysis processes.
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