Software Engineering SMTS

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Job Category

Software Engineering

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

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 including Data, Training, Predictions/scoring, Orchestration, Model Management, Model Storage, Experimentation etc. 

We are already producing over a billion predictions per day, Training 1000s of models per day along with 10s of different Large Language models, serving thousands of customers. We are enabling customers' usage of leading large language models (LLMs), both internally and externally developed, so they can leverage it in their Salesforce use cases. Along with the power of Data Cloud, this platform provides customers an unparalleled advantage for quickly integrating AI in their applications and processes. 

We are looking for Engineering leaders to help us take us to the next level, and build a platform that scales to hundreds of thousands of customers, and hundreds of billions of predictions per day and works on bleeding edge technologies on model training, model inferencing and Generative AI.

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 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

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 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 OpenSearch, DynamoDB, EMR and S3

Preferred Qualifications: 

• Experience working in machine learning, and technologies such as Amazon SageMaker and Google Cloud ML

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

Unleash Your Potential

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.

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Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. 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.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well 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. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.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.

At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $162,800 - $223,900 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $246,000 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.