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.. This includes, but is not limited to, setting up SageMaker instances, creating Docker images, configuring lambda functions, setting up orchestration layer via Airflow, deploying endpoints, and creating API gateways.. Strong programming skills with one or more languages such as Python, PySpark, Apache Spark, Java, JavaSript, C, C. Extensive experience using Snowflake, AWS SageMaker, GCP/GCP BigQuery, DBT, and Airflow for AI/ML model deployment and operationalization.. Familiarity with advanced statistical and machine learning techniques such as clustering, gradient boosting machines (GBM), support vector machines (SVM), neural networks (e.g., ANN, RNN, CNN), and other deep learning algorithms is a plus.

data engineering

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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’re looking for an expert engineering leader to join the Marketing AI Algorithms & Applications team within the Marketing Technology (MarTech) organization. We are driving the vision of AI-powered marketing at Salesforce and we are committed to integrating AI/ML algorithms into marketing decision support systems to optimize marketing spend and operations. The Director, Data & ML Engineering willl be responsible for both data engineering and MLOps engineering teams to support data science applications.
This is a highly visible and impactful role with the ability to directly influence the Salesforce MarTech transformation strategy, operations, and investment allocation! If this sounds like you keep reading for futher details
Responsibilities:
Hire and lead a team of high-caliber data engineers and MLOps engineers including:
Oversee the entire lifecycle of data engineering projects: build scalable, reliable, and high performing data ingestion pipelines that collect, transform, integrate, and load structured, semi-structured, and unstructured data from a variety of sources, such as transactional data, data warehouse, and data lakes.
Oversee the entire lifecycle of ML engineering projects: develop sophisticated AI/ML solution pipelines that automatically score, monitor, and retrain AI/ML models. Test and deploy these AI/ML pipelines in AWS production environment, following CI/CD and release engineering practices. Refactor code to ensure that in-production AI/ML pipelines meet high standards of accuracy and efficiency, as well as robustness and scalability.
Use best practices to design and develop feature stores on Snowflake and other platforms to support rapid AI/ML model development.
Establish strong partnerships across the organization; collaborate with platform teams and system architects to establish a shared ecosystem of platforms required for AI/ML model development, deployment, and system integration. This includes, but is not limited to, setting up SageMaker instances, creating Docker images, configuring lambda functions, setting up orchestration layer via Airflow, deploying endpoints, and creating API gateways.
Enable system observability by developing and monitoring reports/metrics such as server response time, error/job failure rates, resource utilization, and cost tracking. Implement system optimization solutions based on these metrics.
Position Requirements:
Master’s or Ph.D. in an engineering field such as computer science, electrical/software engineering, information technology, or other relevant engineering field.
8-10+ years of building high performing, large-scale, and fault-tolerant data ingestion pipelines. Deep expertise in designing, building, and monitoring ETL/ELT data processes, as well as data modeling, data warehousing, and/or data lakes.
3-5+ years of demonstrated ability developing AI/ML solution pipelines, designed for scalability, repeatability, and process automation using CI/CD framework. Must have multiple examples of managing large, enterprise-level data and ML engineering projects.
3-5+ years leading teams of data engineers and ML engineers with strong focus on technical talent recruitment, management, and retention.
Strong programming skills with one or more languages such as Python, PySpark, Apache Spark, Java, JavaSript, C, C++, C#.
Extensive experience using Snowflake, AWS SageMaker, GCP/GCP BigQuery, DBT, and Airflow for AI/ML model deployment and operationalization.
Strong communicator who will work well with executives and technologists, and influence stakeholders across all levels of the organization.
Understanding of the AI/ML model development and deployment cycle. Familiarity with advanced statistical and machine learning techniques such as clustering, gradient boosting machines (GBM), support vector machines (SVM), neural networks (e.g., ANN, RNN, CNN), and other deep learning algorithms is a plus. Fluency with ML frameworks like Pytorch and Tensorflow is also a plus.


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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 Colorado-based roles, the base salary hiring range for this position is $185,800 to $269,500.
For Washington-based roles, the base salary hiring range for this position is $204,400 to $296,400.
For California-based roles, the base salary hiring range for this position is $223,000 to $323,400.
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.

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