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Lead / Staff ML Engineer

Lead / Staff ML Engineer

SalesforceZapopan, Jalisco, Mexico
Hace 9 días
Descripción del trabajo

Overview

Lead / Staff Machine Learning Engineer role in Mexico City at Salesforce. You will drive state-of-the-art ML solutions for internal marketing platforms, collaborating with Data Science, Data Engineering, Product, and Marketing teams to deliver scalable ML solutions with measurable impact and to accelerate Salesforce's growth.

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. We are 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 (eg, 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 (eg, 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. Know your rights : workplace discrimination is illegal. Salesforce believes in equality and inclusivity and bases decisions on merit, competence and qualifications, without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, disability, veteran status, or other classifications protected by law. This policy applies to current and prospective employees and all employment processes.

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