Software Engineering SMTS

* ** 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.**
* ** Working with Sagemaker, Tensorflow, Pytorch, Triton, Spark, or equivalent large-scale distributed Machine Learning technologies on a modern containerized deployment stack using Kubernetes, Spinnaker, and other technologies**
* ** Experience building Big Data services on AWS, GCP or other public cloud substrates**
* ** Eat, sleep, and breathe services. You have experience balancing live-site management, feature delivery, and retirement of technical debt**
* ** 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 machine learning APIs for Einstein Platform**
* ** Contribute to the long-range plan, and help drive the microservices architectures for machine learning**
* ** 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**
* ** Partner with vendors like AWS and Data Science teams to pick best fit in terms of libraries and compute to deliver cost effective and scalable model hosting and tuning/training capabilities**
* ** 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 leading/working in teams that have built and 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 Open Search, Dynamo

DB, EMR and S3**
* ** Experience working in machine learning, and technologies such as Amazon Sage Maker and Google Cloud ML**
* ** Experience building or leading teams that have built and and run real-time data applications in production
** When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and
* be your best*, and our AI agents accelerate your impact so you can
* do your best*. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey.

It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
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