Lead Member of Technical Staff - Machine Learning Engineering

Salesforce, the #1 AI CRM, is seeking a Lead Member of Technical Staff - Machine Learning Engineering to join its foundation machine learning platform team within the Trust Intelligence Platform organization. The successful candidate will define and execute the technical ML strategy, lead the end-to-end development of ML pipelines, and provide technical leadership in ML engineering best practices.

Responsibilities:

• Define and drive the technical ML strategy, emphasizing robust and performant model architectures and MLOps practices.
• Lead the end-to-end development of ML pipelines, focusing on automated retraining workflows and model optimization for cost and performance.
• Own a portfolio of multiple machine learning pipelines within security and compliance.
• Implement infrastructure-as-code, CI/CD pipelines, and MLOps automation with a focus on model monitoring and drift detection.
• Design and implement comprehensive monitoring solutions for model performance, data quality, and system health.
• Collaborate with Data Science, Data Engineering, Research, and Product Management teams to deliver scalable ML solutions with measurable impact.
• Provide technical leadership in ML engineering best practices and mentor junior machine learning engineers.

Requirements:

• Master's or PhD in a quantitative field.
• Extensive experience (6+ years) in the end-to-end lifecycle of multi-model machine learning systems.
• Deep understanding and practical application of containerization (Docker) and workflow orchestration (Kubernetes, Apache Airflow).
• Mastery of Python programming, including proficiency in leading ML frameworks (TensorFlow, PyTorch).
• Demonstrated success in implementing comprehensive MLOps methodologies.
• Solid foundation in feature engineering techniques and the implementation of feature stores.
• Significant experience in developing and deploying generative AI solutions into production environments.
• Expertise in infrastructure-as-code principles, monitoring tools, and big data technologies (Spark, Snowflake).
• Experience in formulating ML governance policies and ensuring adherence to data security regulations.
• Successfully led machine learning initiatives, consistently delivering significant and quantifiable business outcomes.
• Exceptional collaboration abilities, with a strong capacity to work effectively across Data Science, Platform Engineering, Research, and Product teams.

Benefits:

• Time off programs.
• Medical, dental, vision.
• Mental health support.
• Paid parental leave.
• Life and disability insurance.
• 401(k).
• Employee stock purchasing program.

Salary Range: $172,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $285,800 annually.