Lead/staff Ml Engineer

Job Category

Software Engineering

Job Details

**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 as we know it 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.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place Agentforce is the future of AI, and you are the future of Salesforce.

**Lead/Staff ML Engineer**

Mexico City

We're Salesforce, the Customer Company, inspiring the future of business with AI + Data + CRM and pioneering the next frontier of enterprise AI with AgentForce. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good - you’ve come to the right place.

**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

Accommodations

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.