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SALESFORCECOM INC Senior/Lead ML Engineer in Seattle, Washington

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.Job CategoryProducts and TechnologyJob DetailsThe RoleThe Einstein Platform Apps group is looking for a Lead ML Engineer with a strong software engineering background, to help us take on one of the world's most extensive data sets and transform it into amazing products that feel like magic. You will work on cutting-edge AI applications and products used by millions of people every day.The ProductEinstein Platform Apps helps customers derive immediate business value by tapping into the power of advanced algorithms in an intuitive, secure, and scalable platform. Our mission is to empower technical experts in building data science solutions by removing the engineering complexity out of their way and to help non-technical users by building explainable, ML-driven plug-and-play solutions for their businesses. We are democratizing AI by making our products accessible to non-technical users - this means we have a big focus on model explainability and customer experience, and we are not content with simply providing the most accurate model.Einstein Prediction Builder, one of the products you will work on, operates on any tabular data and can predict both numeric and categorical labels - to learn more, watch this short video: .We also own an open sourced ML learning library sitting on top of Spark (), which powers all of our models and predictions. You will be working in an interdisciplinary team with data scientists, machine learning and software engineers which has end to end ownership of the product - from model quality, to run time performance, and SLA violations. We all work together to build the best possible product we can, and some of your responsibilities will include the following:ResponsibilitiesDefine and build interfaces for new machine learning problemsImplement machine learning flows and pipelines for a seamless end to end experience for the customer, from data processing to prediction servingChampion best engineering practices within the team and wider orgWork heavily across team to leverage shared implementations and designs in order to quickly iterateContribute directly to the Einstein platform that powers 1000s of models and billions of predictions daily in production today!Required SkillsetYou have industry experience with writing code (e.g. Java, Scala, Spark) and taking machine learning models to production. Preference for 4+ years of industry experience. The ideal candidate would have previous experience developing distributed systems powering ML products.We have scale - we have thousands of models that need to be managed, so experience in distributed, scalable systems is preferred. You know how to put modern ML pipelines together using frameworks such as Airflow, Dagster, or others.You have experience working on a platform and integrating with multiple services and teams. You can identify gaps in the platform and provide concise requirements for new features, while finding creative ways to unblock yourself and the team in the mean time.We are a growing, diverse team and we work together on projects. We love to collaborate and help each other, and we want someone to share that ideology.You have to be a very quick learner - we face new challenges every day, anything that ranges between the operating model of a financial services companies, conversation model for chatbots, tinkering with convolutional and recurrent networks, to how to make Spark work with the S3 file system. No school could prepare you for all of these, so you need to be very quick on your feet.AccommodationsIf you require assistance due to a disability applying for open positions please submit a request via this Posting StatementAt Salesforce we believe that the business of

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