Software Engineering SMTS

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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.

*IN SCHOOL OR GRADUATED WITHIN THE LAST 12 MONTHS? PLEASE VISIT FUTURE FORCE FOR OPPORTUNITIES*

Einstein products & platform democratizes AI and transforms the way our Salesforce Ohana builds trusted machine learning and AI products - in days instead of months. It augments the Salesforce Platform with the ability to easily create, deploy, and manage Generative AI and Predictive AI applications across all clouds. We achieve this vision by providing unified, configuration-driven, and fully orchestrated machine learning APIs, customer-facing declarative interfaces and various microservices for the entire machine learning lifecycle.

Einstein Studio makes it faster and easier to run and deploy enterprise-ready AI across every part of the business, bringing trusted, open, and real-time AI experiences to every application and workflow. With Einstein Studio, companies can leverage their proprietary, real-time customer data from Data Cloud to train AI models that solve specific business needs. And with Einstein Studio's BYOM solution, companies can train their preferred AI model with Data Cloud, which connects all customer data from any source, and automatically harmonizes that data into a single customer profile that adapts to each customer's activity in real time for use across any department.

The ideal candidate will be:
Technical - We don't expect you to be the most technical person on your team, but there is a pretty high minimum bar that you must pass to be useful to the team, and help influence the team to make the right technical decisions.
A Leader - You are a natural leader, who can mentor and coach engineers on the team to be able to handle bigger challenges, find fulfillment in their work, and execute on the product growth goals through collaboration to do the best work of their lives.
Experienced - We will need you to bring that experience. We want the best people who spend large portions of their time thinking about how to design large scale distributed Machine Learning services.

Responsibilities:

• Working with a large-scale distributed platform, designing and managing data & metadata models.

• Partner with Product Managers, Architects and Data Scientists to understand customer requirements, and help translate requirements to working software.

• Own the technology for fully orchestrated APIs for Salesforce AI Platform.

• Contribute to the long-range plan, and help drive the microservices architectures for machine learning.

• Designing, developing, debugging UI components.

• Designing, developing, debugging, and operating resilient distributed systems that run across thousands of compute nodes in multiple datacenters.

• Participate in the team's on- call rotation to address complex problems in real-time and keep services operational and highly available.

• Create and enforce processes that ensure quality of work, and drive engineering excellence.

• Exhibit a customer-first mentality while making decisions, and be responsible and accountable for the output of the team.

Core Qualifications:

• BS, MS, or PhD in computer science or a related field, or equivalent work experience.

• 5+ years of hands-on experience with big data, machine learning, and microservices architectures.

• Track record of leading highly impactful projects from conception to finish.

• Expertise in JVM based languages (Java, Scala) and Python.

• Experience working with UI technologies.

• Experience leading/working in teams that have built and run machine learning services, such as for training & inferences, at scale for predictive and generative models.

• Experience with open source projects such as Spark, Kafka, Feast, Iceberg.

• Experience in building software on AWS cloud computing such as OpenSearch, DynamoDB, EMR and S3.

Preferred Qualifications:

• Experience building or leading teams that have built and run real-time data applications in production.

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