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Full-Time

Field Engineering

Generative AI Product Specialist

Posted on 7/11/2024

Databricks

Databricks

5,001-10,000 employees

Unified data platform for analytics and AI

Data & Analytics
Enterprise Software
AI & Machine Learning

Compensation Overview

$169k - $299kAnnually

+ Equity Awards

Expert

Remote in USA

Category
Applied Machine Learning
AI & Machine Learning
Required Skills
Kubernetes
Microsoft Azure
Python
Data Science
Pytorch
AWS
Natural Language Processing (NLP)
Google Cloud Platform
Requirements
  • 10+ years of engineering and pre-sales customer facing experience
  • ML experience as either an engineer or researcher
  • Strong software engineering skills with expertise in Python
  • Experience in a fast-paced, entrepreneurial environment
  • Expertise with enterprise cloud environments (AWS, Azure, GCP, OCI), technologies (e.g., kubernetes, containers), and the ML focused hardware accelerators (Nvidia A100s and H100s, AMD MI series, etc.)
  • Experience with Mosaic Composer and other ML technologies and frameworks (e.g., PyTorch)
  • Outstanding skills in presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos
  • Strong aptitude and willingness to learn and excel in new technologies and push the envelope of what is possible
  • Strong verbal and written communication skills and ability to lead effectively across organizations both internally and with customers
  • A minimum of a bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or equivalent experience through demonstrable work experience
  • Nice to have: experience in fast-growing startups in the AI space with a focus on GenAI, NLP, CV, and diffusion models.
Responsibilities
  • Lead the enablement, expertise, and backline support for the customer-facing field team for Generative AI
  • Represent the product internally to field engineering teams and externally to the market via speaking at conferences, online webinars, and blog posts
  • Recruit, lead, encourage, and reward a group of specialists across the field dedicated to enabling Generative AI use cases on Databricks
  • Work hands-on with deeply technical customers as the engineering/research liaison to demonstrate and communicate Databricks’ GenAI products and value
  • Create and execute compelling demos to showcase Mosaic AI to specific customer’s industries and use cases by compiling data sets, data wrangling, model training, and communicating results
  • Support customers by assisting with initial model scoping and creation
  • Partner closely with sales and other Mosaic AI leaders to grow thought leadership and drive customer success
  • Proactively automate tasks as needed and partner closely with the product, engineering, and research teams to bring back information and ideas to drive the products forward
  • Define customer requirements and definitions, build demos, assist with proposals, solution briefs, and bring in professional services when needed
  • Participate in pre-sales on-site visits and be the go-to technical point person for initial customer interaction

Databricks provides a unified platform that combines data lakes and data warehouses, known as lakehouse architecture, allowing organizations to manage, analyze, and gain insights from their data effectively. The platform is designed for a variety of users, including data engineers, data scientists, and business analysts, and is applicable across multiple industries such as finance, healthcare, and technology. Databricks offers features like automated ETL processes, secure data sharing, and high-performance analytics, which help streamline data management and analysis. Additionally, it supports machine learning and AI workloads, enabling users to build and deploy models at scale. Unlike many competitors, Databricks operates on a subscription-based model, generating revenue through platform access and professional services. The company's goal is to empower organizations to leverage their data for better decision-making and insights.

Company Stage

Series I

Total Funding

$4.2B

Headquarters

San Francisco, California

Founded

2013

Growth & Insights
Headcount

6 month growth

9%

1 year growth

25%

2 year growth

80%
Simplify Jobs

Simplify's Take

What believers are saying

  • The $1 billion acquisition of Tabular is likely to enhance Databricks' data management capabilities and market reach.
  • The development and launch of the DBRX generative AI model, with a $10 million investment, underscores Databricks' dedication to leading in AI technology.
  • High-profile investments from figures like Nancy Pelosi indicate strong confidence in Databricks' growth potential.

What critics are saying

  • The integration of Tabular's team and technology could face challenges, potentially disrupting operations.
  • The competitive landscape in AI and data analytics is intense, with major players like Google and Microsoft posing significant threats.

What makes Databricks unique

  • Databricks' acquisition of Tabular, founded by the creators of Apache Iceberg, strengthens its position in the open lakehouse market.
  • The launch of DBRX, an open-source LLM that outperforms GPT-3.5 and Llama 2, showcases Databricks' commitment to cutting-edge AI innovation.
  • Strategic partnerships, such as with AVEVA for industrial AI, highlight Databricks' ability to integrate and enhance diverse technological ecosystems.

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Benefits

Extended health care including dental and vision

Life/AD&D and disability coverage

Equity awards

Flexible Vacation

Gym reimbursement

Annual personal development fund

Work headphones reimbursement

Employee Assistance Program (EAP)

Business travel accident insurance

Paid Parental Leave

INACTIVE