Lead Machine Learning Engineer - LMTS

About the role

The Lead Member of Technical Staff - Machine Learning Engineering position is within the Trust Intelligence Platform organization at Salesforce. This role focuses on building and accelerating scalable and resilient machine learning pipelines for the security engineering organization.

Responsibilities

• Shape the defense strategy by translating vague security threats into concrete mathematical problems.
• Lead the evolution of threat detection, incorporating advanced probabilistic modeling, graph analytics, and supervised and unsupervised learning.
• Elevate the organization by mentoring junior scientists and engineers, building internal tooling, and influencing the broader security engineering roadmap.
• Operationalize intelligence by delivering production-grade models that the Security Operations Center (SOC) trusts, minimizing "alert fatigue" and maximizing analyst efficiency.

Requirements

• Extensive experience (3-5+ years) in data science, with at least 2+ years dedicated to the cybersecurity domain.
• Hands-on comfort with high-volume logs and proficiency with Spark/Pyspark, Snowflake, Flink, and streaming services like Apache Kafka.
• Mastery of Python programming, including proficiency in leading ML frameworks (TensorFlow, PyTorch), and adherence to software engineering best practices.
• Mastery of feature engineering techniques and the implementation of feature stores.
• Experience in formulating ML governance policies and ensuring adherence to data security regulations.
• Ability to explain complex statistical concepts to non-technical stakeholders and executive leadership.
• Proven ability to manage scope, timelines, and stakeholder expectations across multiple organizations.
• High degree of autonomy with the ability to look at a vague business problem and structure a data-driven solution without needing a predefined roadmap.

Preferred Skills

• Masters or PhD in a quantitative field.
• Expertise in advanced Natural Language Processing (NLP) methodologies.
• Experience contributing to open-source security data science tools.
• Presentations at major security conferences (Black Hat, DEF CON, BSides) or data conferences.
• Background in offensive security (Penetration Testing/Red Teaming) with an "attacker's mindset."
• Demonstrated experience conducting research or working collaboratively with Machine Learning (ML) research teams.
• Previous experience in a mentoring role for junior engineers.
• Track record of publications and/or patents in quantitative disciplines.

Benefits

At Salesforce, we offer a comprehensive benefits package including time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. For more details, visit this link.

Pay

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

Schedule

Full-time position.