Facebook pixel

Sales Engineer
Confirmed live in the last 24 hours
Locations
Remote • United States
Experience Level
Entry
Junior
Mid
Senior
Expert
Requirements
  • Strong intellectual curiosity, especially around being able to map business problems to systems that leverage machine learning
  • Experience in technical pre-sales or consulting in a fast paced environment preferred but not required
  • Excellent communication and presentation skills, and comfortable talking to all levels of customer teams, from individual contributors to C-level executives
  • Programming language(s) proficiency (preferably Python;, R, SQL, Java, Scala, Julia.)
  • Knowledge of data science/machine learning algorithms (ex. supervised, semi-supervised, unsupervised, classical, deep learning), their applications and drawbacks
  • Experience with cloud services (AWS, Azure, GCP)
  • Understanding of the machine learning lifecycle (feature generation, model training, model deployment, batch and real time scoring, monitoring, and maintenance) and engineering (“MLops”) considerations
  • Working knowledge of data storage technologies and formats (RDBMS, HDFS, parquet…)
  • Experience configuring on-prem applications in an enterprise security environment
  • Hands on experience with computational resources and frameworks (Docker, Kubernetes, Spark)
  • Knowledge of data workflow management tools, such as Kubeflow, Airflow, Luigi, etc
Responsibilities
  • Serve as trusted technical advisor to prospective customers and become an expert on Dataiku's product offerings
  • Communicate and showcase Dataiku's business and technical value proposition, technical differentiation, and integration points with existing customer technical ecosystem/workflows
  • Drive technical sales relationships and own the customer's success during presales activities
  • Partner with Account Executive, Business Development Representative and Sales Management Team to qualify revenue opportunities
  • Communicate customer priorities across cross-functional teams at Dataiku, including Product, Engineering, Marketing, and Customer Success
  • Lead discovery meetings to understand and uncover customer business/technical challenges and existing technology stack
  • Conduct and coordinate Dataiku demonstrations, Proofs-of-Concept (POC), and evaluations to demonstrate the business value articulated in the usage scenarios to prove that Dataiku delivers the needed value and ROI better than our competitors
  • Coordinate company-wide resources to drive technical engagements forward and provide answers/guidance to customer's questions
  • Influence roadmap and GTM decisions, infusing prospective customer priorities into every decision we make
  • Support and strategize with partner networks to expand Dataiku support within customers
  • Assist in sales pipeline building activities including attendance at live and/or virtual trade-shows and industry conferences, working with marketing / partners on webinars, events, and other activities specified by sales and sales engineering management
Dataiku

1,001-5,000 employees

Enterprise AI & ML platform
Company Overview
Dataiku’s mission is to pioneer everyday AI by helping everyone in an organization – from technical teams to business leaders – use data to make better decisions and drive business value on a daily basis. The company has developed a platform that systemizes the use of data and AI to enable organizations to customize, share, and reuse AI components and apps to easily deliver high-quality projects and streamline the path to production.
Benefits
  • Health, life & pension benefits
  • Equity
  • Time off for R&R
  • Public holidays
  • Work from anywhere policy (unique to team)
  • 12 weeks of paid parental leave
  • Volunteering opportunities
  • Career Development opportunities
  • Technology stipend
  • Onsite meals & healthy snacks
  • Office happy hours
  • Company-wide events
Company Core Values
  • Diversity of People & Perspectives
  • Tolerance & Open-Mindedness
  • Accountable Camaraderie
  • Work-Life Balance
  • Dedication to Learning
  • Conscious Long-Term Responsibility