Staff ML Engineer

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Job Category

Software Engineering

Job Details

About Salesforce

We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. 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.

We are seeking an experienced Lead / Staff Machine Learning Engineer to support the development and deployment of high-impact ML model pipelines that measurably improve marketing performance and deliver customer value. In this critical role, you will collaborate closely with Data Science, Data Engineering, Product, and Marketing teams to lead the design, implementation, and operations of end-to-end ML solutions at scale. As a hands-on technical leader, you will own the MLOps lifecycle, establish best practices, and mentor junior engineers to help grow a world-class team that stays at the forefront of ML innovation. This is a unique opportunity to apply your passion for ML and to drive transformative business impact for the world's #1 CRM provider, shaping the future of customer engagement through AgentForce - our groundbreaking AI agents that are setting new global standards for intelligent automation.

Responsibilities

• Define and drive the technical ML strategy with emphasis on robust, performant model architectures and MLOps practices
• Lead end-to-end ML pipeline development focusing on automated retraining workflows and model optimization for cost and performance
• Implement infrastructure-as-code, CI/CD pipelines, and MLOps automation with focus on model monitoring and drift detection
• Own the MLOps 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
• Design and implement comprehensive monitoring solutions for model performance, data quality, and system health
• 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 MLOps principles

 

• 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 MLflow, for comprehensive ML experiment tracking and model lifecycle management
• Deep expertise in containerization and workflow orchestration (Docker, Kubernetes, 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
• Strong background in feature engineering and feature store implementations using cloud-native technologies
• Expert in infrastructure-as-code, monitoring solutions, and big data technologies (Spark, Snowflake)
• Experience defining ML governance policies and ensuring compliance with data security requirements
• 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

Accommodations

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Posting Statement

At Salesforce we believe that the business of business is to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects society through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more. Learn more about Equality at www.equality.com and explore our company benefits at www.salesforcebenefits.com.

Salesforce is an Equal Employment Opportunity and Affirmative Action Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Salesforce does not accept unsolicited headhunter and agency resumes. Salesforce will not pay any third-party agency or company that does not have a signed agreement with Salesforce.

Salesforce welcomes all.

Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.

For California-based roles, the base salary hiring range for this position is $200,800 to $276,100.

For Illinois based roles, the base salary hiring range for this position is $184,000 to $253,000.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, benefits. More details about our company benefits can be found at the following link: https://www.salesforcebenefits.com.