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Join to apply for the Senior Machine Learning Eng role at Salesforce in Mexico City. We’re looking for a Lead / Staff Machine Learning Engineer to design, build, and deploy high-impact ML model pipelines that improve marketing performance and deliver customer value. This role collaborates closely with Data Science, Data Engineering, Product, and Marketing teams, owns the ML lifecycle, establishes best practices, and mentors junior engineers. About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword – it’s a way of life. The world of work is changing and we’re looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce’s core values at the heart of it all. Responsibilities Define and drive the technical ML strategy with emphasis on robust, performant model architectures and MLOps practices Own the ML lifecycle, including model governance, testing standards, and incident response for production ML systems Establish and enforce engineering standards for model deployment, testing, version control, and code quality Implement infrastructure-as-code, CI/CD pipelines, and ML automation with focus on model monitoring and drift detection Design and implement comprehensive monitoring solutions for model performance, data quality, and system health Lead end-to-end ML pipeline development focusing on optimizing model cost and performance as well as automating training workflows Collaborate with Data Science, Data Engineering, and Product Management teams to deliver scalable ML solutions with measurable impact Provide technical leadership in ML engineering best practices and mentor junior engineers in ML and MLOps principles Position Requirements MS or PhD in Computer Science, AI/ML, Software Engineering, or related field 8+ years of experience building and deploying ML model pipelines at scale, with focus on marketing use cases Expert-level knowledge of AWS services, particularly SageMaker and related services Deep expertise in containerization and workflow orchestration (e.g., Docker, Apache Airflow) for ML pipeline automation Advanced Python programming with expertise in ML frameworks (TensorFlow, PyTorch) and software engineering best practices Proven experience implementing end-to-end MLOps practices including CI/CD, testing frameworks, and model monitoring Expert in infrastructure-as-code, monitoring solutions, and big data technologies (e.g., Snowflake, Spark) Experience implementing ML governance policies and ensuring compliance with data security requirements Familiarity with feature engineering and feature store implementations using cloud-native technologies Track record of leading ML initiatives that deliver measurable marketing impact Strong collaboration skills and ability to work effectively with Data Science and Platform Engineering teams Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to shape the future — and redefine what’s possible — for yourself, for AI, and the world. Accommodations If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form. Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education. Referrals increase your chances of interviewing at Salesforce by 2x #J-18808-Ljbffr
