Arize AI - AI Sales Engineer, (EMEA)
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Requirements
• You can empathize with the frame of reference of who you are communicating with and tailor your message and approach accordingly. • Ability to simplify complex, technical concepts • A quick and self learner: • You are undaunted by the technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV. • You ask the right questions with the customer to uncover nuances in their unique deployments. • Ability to work within ambiguity and take action with limited direction • Knowledgeable in Machine Learning: • You may not have a PhD in ML but you know the difference between Linear Regression and Boosted Trees and the advantages / disadvantages of each. • You have some experience training models in common packages such as scikit-learn, HuggingFace, fastai, and etc. • 5+ years within customer facing role: • 5+ years within customer facing role • Pre-sales, technical account management, or consulting experience • Worked with customers within the high enterprise (e.g. Fortune 500, etc) • Proficiency in: • Proficiency in: • Previous experience working across and aligning Sales, Product, and Engineering • Previous experience within a team that underwent a high growth stage • Previous engineering experience in: Data Engineering, MLOps, Kubernetes, GCP / AWS / Azure • The estimated annual salary and variable compensation for this role is between $140,000 - $230,000, plus a competitive equity package. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support. • While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces.
Responsibilities
• You are the trusted advisor to the customer: • Build relationships with technical stakeholders • Lead product demonstrations of the Arize platform • Lead discovery to understand prospect’s ML stack to collaborate with the Sales team to construct a compelling value proposition of the Arize Platform • Handle technical objections and develop strategies across sales, engineering, and product to unblock them • Act as a Domain Expert within AI/ML: • Write educational and compelling blog posts about ML and MLOps related topics • Collaborate to create and enhance documentation, recorded video assets and other publically available as well as internal enablement materials • Engage in relevant ML communities online to raise awareness on challenges of deploying ML in production
Benefits
• None explicitly stated in this job posting.
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