[Remote] AI Sales Engineer at Arize AI

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Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, AI & Machine Learning, Software as a Service (SaaS)Industries

Skills

Key technologies and capabilities for this role

AIMLDeep LearningCustomer Relationship BuildingProduct DemonstrationTechnical Stakeholder EngagementProof of Concept DevelopmentObjection HandlingEducational Content Creation

Questions & Answers

Common questions about this position

What experience level is required for the customer-facing aspect of this role?

The role requires 5+ years in a customer-facing role, such as pre-sales, technical account management, or consulting, with experience working with high enterprise customers like Fortune 500 companies.

What technical proficiencies are required for this position?

Proficiency in Python and Linux/Unix is required, along with knowledge in Machine Learning such as understanding Linear Regression vs. Boosted Trees and experience training models with packages like scikit-learn, HuggingFace, or fastai.

What are the key soft skills needed for this AI Sales Engineer role?

Strong communication skills to empathize, tailor messages, and simplify complex concepts are essential, along with being a quick self-learner who thrives in ambiguity, asks the right questions, and develops their own point of view on production ML deployments.

What is the team like at Arize AI?

The engineering team is composed of industry veterans with experience in deep learning infrastructure, autonomous drones, ridesharing marketplaces, and ad tech, building systems that interact with complex production software.

What makes a strong candidate stand out for this role?

Candidates with 5+ years in customer-facing roles in high enterprise settings, ML knowledge, Python/Linux proficiency, strong communication, and quick learning in ambiguous environments will stand out; bonus for experience aligning Sales/Product/Engineering, high-growth teams, or data engineering.

Arize AI

AI observability and model evaluation platform

About Arize AI

Arize AI provides a platform focused on AI observability and evaluating language models. The platform allows companies to monitor, troubleshoot, and assess the performance of various machine learning models, including those used for natural language processing, computer vision, and recommendations. Users can access analytics and workflows that help identify and resolve issues within their AI systems, ensuring optimal performance. Key features include task-based evaluations for aspects like hallucination and relevance, as well as tools for visualizing query and knowledge base embeddings to enhance retrieval accuracy. Unlike many competitors, Arize AI specifically targets the needs of top AI companies, offering tailored solutions for continuous improvement of their models. The goal of Arize AI is to empower these companies to enhance their AI capabilities through effective monitoring and evaluation.

Berkeley, CaliforniaHeadquarters

2020Year Founded

$59.3MTotal Funding

SERIES_BCompany Stage

Data & Analytics, AI & Machine LearningIndustries

51-200Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Retirement Plan

Unlimited Paid Time Off

Parental Leave

Mental Health Support

Flexible Work Hours

Risks

Competition from tech giants like Microsoft may overshadow Arize's offerings.

Rapid tech advancements could render Arize's features obsolete if not updated.

Data privacy compliance in the EU poses challenges for Arize AI.

Differentiation

Arize AI offers industry-first AI Copilot for troubleshooting AI systems.

The platform provides unique prompt engineering and retrieval tracing workflows.

Arize AI supports EU data residency, addressing regional data privacy concerns.

Upsides

Increased demand for AI observability tools boosts Arize AI's market potential.

Collaboration with Microsoft enhances Arize AI's enterprise deployment capabilities.

Prompt variable monitoring highlights Arize AI's commitment to LLM performance enhancement.

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