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Job Information, Inc Software Engineering Architect, ML Platform in Boston, Massachusetts

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Job Category

Products and Technology

Job Details

Salesforce Einstein is seeking a Machine Learning Engineering Architect to help us deliver on our next generation AI/ML Platform for Salesforce. You will work on designing and bringing world-class ML to production on products used by used by millions of people every day. You will be working with a team of fellow data scientists, machine learning engineers, software developers, product managers and designers and will be part of an awesome team that will driving the future of next generation data-platform for AI applications

We are building the next generation AI/ML Platform for Salesforce to support the many different needs of the AI/ML workloads that power our CRM applications and automate, assist and provide insights to our customers through state of the art AI technologies. Our mission is to build a multi-tenant, scalable, secure, cloud-agnostic and performant platform that caters to the spectrum of needs from real-time request/response scoring to stream and batch scoring for autoML, Deep Learning, and traditional machine learning use cases. We work on structured and unstructured text, image, and voice data and launch large scale training and scoring workloads to create AI models that are used to power the intelligence in our CRM applications.

The Einstein Platform democratizes AI and transforms the way our Salesforce Ohana builds trusted machine learning products - in days instead of months. The Einstein Platform augments the Salesforce Platform with the ability to easily create, deploy, and manage predictive applications across all CRM applications. We achieve this vision by providing unified, configuration-driven, and fully orchestrated machine learning APIs and customer-facing declarative interfaces. We are already producing over a billion predictions per day serving thousands of customers.

Ethical AI is a core tenet of Salesforce’s AI efforts and support for model observability, fairness, explainability and other ethical considerations are available as platform capabilities in this next generation ML platform. Agility for data scientists and support for quick iteration, fast experimentation and a low friction and scalable path to production is facilitated along with common flexible and reusable tools to quickly onboard new use cases.

In addition to technical skills and data fluency/analytical skills, an ideal candidate is also a great cross-functional collaborator. Working within this large organization and at the scale of delivery, you invest in communication to build alignment and influence others to help deliver what is necessary to bring world-class AI to production for our customers.


Design and deliver high-impact machine learning solutions to our customers across a breadth of use cases

  • Contribute to the long-range plan, and build the technology for taking the Einstein Platform to hundreds of thousands of Salesforce customers, and hundreds of billions of predictions per day

  • Develop compute and data infrastructure that ingests and transforms data from different sources and customers at scale in batch and real-time

  • Build large-scale data pipelines and computation systems that process massive amount of data

  • Build multi-tenant RESTful services for low-latency scoring/inferences at scale, and training massive amounts of data

  • Work with multiple experienced teams, identifying opportunities for improving our multi-tenant machine learning pipelines. This includes internal product teams to help them bring machine learning into their products

  • Bring new technologies and frameworks to our teams. Collaborating with platform engineering to help guide and design solutions for new machine learning services, tools and approaches for multi-product, multi-tenant solutions

Participate in early ideation and development

  • Learn about how Salesforce customers use our applications, and find new, high-impact methods to deliver business value to our customers

  • Partner end-to-end with Product Managers, Application Architects, Data Scientists, Designers and and Researchers where appropriate to understand customer requirements, design prototypes, and bring innovative technologies to production

  • Help nurture an environment of learning and rapid iteration.

Additional Responsibilities/Duties

  • Design solutions that are enterprise scalable and maintainable. Able to consider a breadth of data use cases

  • Drive strategic technology initiatives, working with Product Managers, other Architects,, Engineers,, SME's and the broader Salesforce organization

  • Work in a consultative fashion to improve communication, collaboration and alignment amongst teams inside and outside of the organization.

  • Analyze and provide feedback on product strategy

  • Provide input into long-range product requirements, best practices, and operational guidelines, with focus on continuous improvement of platform reliability and serviceability

  • Drive research, case studies, and prototypes on leading edge technologies and how they can be leveraged

  • Ensure that we are continuously raising our standard of engineering excellence

Ideal Candidate

The Ideal candidate is an industry expert in modern data systems and possesses the following attributes:

  • Technical excellence

  • An expert in modern data architectures, including data pipelines for the purposes of analytics and machine learning. Experience with regulated and enterprise environments is key. Have a deep understanding of business and product context, and able to work with engineering teams on solutions that are a right fit for Salesforce Einstein.

  • Have a deep expertise in large-scale distributed storage and database systems and strong experience in building large-scale, high-performant data processing systems

  • Have a comprehensive responsibility for the overall architecture of Einstein’s data platform.

  • Key arbitrator in future buy vs. build decisions, as well as due-diligence in matters of adoption and acquisition.

  • Work with legal counsel when necessary on matters of regulatory compliance.

  • Strategic excellence

  • Partner with Product leadership to shape and help drive the direction of Einstein’s data platform.

  • Work with executive leadership on long-term technology roadmap, aligning technical and business strategies.

  • Build the technology for taking the Einstein Platform to hundreds of thousands of Salesforce customers, and hundreds of billions of predictions per day

  • Communication excellence

  • Be a vocal advocate for Einstein’s technology at the highest levels of Salesforce architecture groups. Work with the office of the CTO to fine-tune the right fit of Einstein’s technology within Salesforce.

  • Facilitate forums for cross-teams discussions of technology and methodology that promote consistency of development and tooling as needed.

  • Work with teams across Salesforce to ensure smooth on-boarding and client experience with the Einstein data platform.

  • Other Skills and Experience

  • Deep understanding in big data architecture and experience in building pipelines(batch/streaming) with some production-grade big data systems such as Hadoop, HDFS, Hive, Spark, Storm and Presto

  • Expert in designing data models for optimal storage and retrieval to meet critical product and business requirements

  • Expert in both SQL database like Postgres, MySQL and No SQL like HBase, Cassandra, Dynamo db

  • Experience in designing highly scalable, robust, and fault-tolerant micro-services

  • Experience in building software on AWS cloud computing such as EMR and S3 and Heroku

  • Mastery in multiple machine learning/AI methodologies

  • Comfortable programming in multiple languages (Java, Scala, Python), and navigating multiple services in a platform

  • Experience using workflow orchestrators such as Airflow

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

  • History of contributions to Hadoop, Spark, Storm, Hadoop, or similar open source projects

  • Experience with containerization technology, such as docker, kubernetes

  • 7+ years of experience bringing Machine Learning to production with a PhD/MS in relevant field or 10+ years experience with a Bachelors

  • Ability to architect, design and deliver large complex projects

  • Ability to provide (informal) coaching to team members to support their understanding of the architecture and aid in their technical development

  • Experience with Agile development methodology (e.g., Scrum)

  • Ability to work with other architects, principal architects, and Chief Technology Officers to shape the architectural vision and roadmap for the organization.

  • Ability to drive long-term design strategies that span multiple complex projects, deliver technical reports and performance presentations to customers and at industry events

  • Ability to create an environment for honest and open discussion of all issues. You involve the right people, from your team and others, to resolve critical issues.

Reference Blog Posts

  • ML Lake: Building Salesforce’s Data Platform for Machine Learning (

  • Flow Scheduling for the Einstein ML Platform

  • Real-time Predictions in a Multitenant Environment (

  • Training & Experimentation: A Next-Generation Generic ML Training and Data Science Platform for Salesforce Einstein


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