About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. The company is looking for people passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Agentforce is the future of AI.
The Experience
We are a foundation machine learning platform team within the Trust Intelligence Platform organization with a main focus to build and accelerate scalable and resilient machine learning pipelines across the security engineering organization.
We are seeking a highly motivated, hands-on lead machine learning engineer with strong business understanding to define and execute the technical ML strategy. This role involves full lifecycle development and optimization of ML pipelines, with a strong focus on MLOps, infrastructure-as-code, CI/CD, and thorough monitoring. The lead will manage multiple ML pipelines, work closely with cross-functional teams, mentor others, and requires deep expertise in various ML technologies to deliver measurable business impact within a security and compliance framework. A critical component of this role is the proven ability to productize Generative AI solutions and agentic workflows to actively enhance the security posture and resilience for the organization and all Salesforce customers.
What You'll Actually Be Doing
•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.
You're Our Person If...
•Masters or PhD in a quantitative field
•Extensive experience (6+ years) in the end-to-end lifecycle of multi-model machine learning systems, from design and development to large-scale deployment.
•Deep understanding and practical application of containerization (Docker) and workflow orchestration (Kubernetes, Apache Airflow) for automated ML pipelines.
•Mastery of Python programming, including proficiency in leading ML frameworks (TensorFlow, PyTorch) and adherence to software engineering best practices.
•Demonstrated success in implementing comprehensive MLOps methodologies, encompassing CI/CD pipelines, testing protocols, and model performance monitoring.
•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.
Even Better If...
•Expertise in advanced Natural Language Processing (NLP) methodologies.
•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.
Compensation
Salesforce believes in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. 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 for this role is $207,800 - $285,800 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.
Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits 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.
