{"@context":"schema.org","@type":"JobPosting","hiringOrganization":{"@type":"Organization","name":"Databricks","logo":"https://s2-recruiting.cdn.greenhouse.io/external_greenhouse_job_boards/logos/400/028/100/resized/Careers_at_Databricks.jpg?1682965270"},"title":"Field Engineering, Mosiac AI Product Specialist ","datePosted":"2024-05-08","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Chicago, Illinois, United States","addressRegion":"IL","addressCountry":null,"postalCode":null}},"description":"\u003cp data-pm-slice=\"1 1 []\"\u003eFEQ125R71\u003c/p\u003e\n\u003cp\u003eWhile candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations.\u003c/p\u003e\n\u003cp\u003eThe Product Specialist for Generative AI will lead the enablement, expertise, and backline support for our customer-facing field team for Generative AI. This will include supporting RAG (retrieval augmented generation) POCs, open source models like Llama2, MPT, Mistral, DBRX and fine-tuning and pre-training custom models as well as using 3rd party models including OpenAI, Anthropic or Mistral. Knowledge of Vector Indexing and Distributed Pytorch is a plus.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYou will represent the product internally to our field engineering teams, and externally to the market via speaking at conferences, online webinars, and blog posts.\u0026nbsp; You will meet with customers to communicate the vision and gather feedback.\u003c/p\u003e\n\u003cp\u003eYou will not have any direct reports but will recruit, lead, encourage, and reward a group of specialists across the field dedicated to enable Generative AI use cases on Databricks.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYou have expertise in Data Science, Machine Learning, Generative AI, NLP and Computer Vision and expertise in using PySpark and SQL.\u0026nbsp; You will excel in distilling product features into a compelling value proposition and enabling Account Executives and Field Engineers to communicate the value in a way through content and demonstrations.\u003c/p\u003e\n\u003cp\u003eThe impact you will have:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eBe a technical expert on all aspects of the Mosaic AI family of products with awareness for the Databricks Data Intelligence Platform and the broader ecosystem\u003c/li\u003e\n\u003cli\u003eWork hands-on with deeply technical customers as the engineering/research liaison to demonstrate and communicate Databricks’ GenAI products and value\u003c/li\u003e\n\u003cli\u003eEmbed and partner closely with the Mosaic AI engineering and research teams and be an extension of them when interfacing with customers and prospects\u003c/li\u003e\n\u003cli\u003eDive into a customer’s code to help them get going on the product(s) or unstick them so they can get started\u003c/li\u003e\n\u003cli\u003eCreate and execute compelling demos to showcase Mosaic AI to specific\u0026nbsp; customer’s industries and use cases by compiling data sets, data wrangling, model training, and communicating results\u003c/li\u003e\n\u003cli\u003eSupport your customers by assisting with initial model scoping and creation\u003c/li\u003e\n\u003cli\u003ePartner closely with sales and other Mosaic AI leaders to grow thought leadership and drive customer success\u003c/li\u003e\n\u003cli\u003eProactively automate tasks as needed and partner closely with the product, engineering, and research teams to be their eyes and ears in the field and bring back information and ideas to drive the products forward\u003c/li\u003e\n\u003cli\u003eBe comfortable with defining customer requirements and definitions - building demos, assisting with proposals, solution briefs, and bringing in professional services when needed\u003c/li\u003e\n\u003cli\u003eStrive in uncomfortable situations with ambiguity and uncertainty in the best way to help solve customer problems\u003c/li\u003e\n\u003cli\u003eWork with sales and other stakeholders, including partners to jointly define solutions\u003c/li\u003e\n\u003cli\u003eParticipate in pre-sales on-site visits and be the go-to technical point person for initial customer interaction\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eWhat we look for:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e10+ years of engineering and pre-sales customer facing experience\u003c/li\u003e\n\u003cli\u003eML experience as either an engineer or researcher\u003c/li\u003e\n\u003cli\u003eStrong software engineering skills with expertise in Python\u003c/li\u003e\n\u003cli\u003eExperience in a fast-paced, entrepreneurial environment\u0026nbsp;\u003c/li\u003e\n\u003cli\u003eExpertise with enterprise cloud environments (AWS, Azure, GCP, OCI),\u0026nbsp; technologies (e.g., kubernetes, containers), and the ML focused hardware accelerators (Nvidia A100s and H100s, AMD MI series, etc.)\u003c/li\u003e\n\u003cli\u003eExperience with Mosaic Composer and other ML technologies and frameworks (e.g., PyTorch)\u003c/li\u003e\n\u003cli\u003eOutstanding skills in presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos\u003c/li\u003e\n\u003cli\u003eStrong aptitude and willingness to learn and excel in new technologies and push the envelope of what is possible\u0026nbsp;\u003c/li\u003e\n\u003cli\u003eStrong verbal and written communication skills and ability to lead effectively across organizations both internally and with customers\u003c/li\u003e\n\u003cli\u003e​​A minimum of a bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or equivalent experience through demonstrable work experience\u003c/li\u003e\n\u003cli\u003eNice to have: experience in fast growing startups in the AI space with a focus on GenAI, NLP, CV, and diffusion models.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eBenefits:\u003c/p\u003e\n\u003cul class=\"ak-ul\" data-indent-level=\"1\"\u003e\n\u003cli\u003e\n\u003cp data-renderer-start-pos=\"3078\"\u003e401(k) Plan\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp data-renderer-start-pos=\"3093\"\u003eEquity awards\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp data-renderer-start-pos=\"3110\"\u003eFlexible time off\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp data-renderer-start-pos=\"3131\"\u003ePaid parental leave\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp data-renderer-start-pos=\"3154\"\u003eFamily Planning\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp data-renderer-start-pos=\"3173\"\u003eGym reimbursement\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp data-renderer-start-pos=\"3194\"\u003eAnnual personal development fund\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp data-renderer-start-pos=\"3230\"\u003eEmployee Assistance Program (EAP)\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAbout Databricks\u003c/p\u003e\n\u003cp\u003eDatabricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on \u003ca href=\"https://twitter.com/databricks\"\u003eTwitter\u003c/a\u003e, \u003ca href=\"https://www.linkedin.com/company/databricks\"\u003eLinkedIn\u003c/a\u003e and \u003ca href=\"https://www.facebook.com/databricksinc\"\u003eFacebook\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eOur Commitment to Diversity and Inclusion\u003c/p\u003e\n\u003cp\u003eAt Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity

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