AI Solutions Engineer

🕒 April 14

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Arize AI

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2019

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

Artificial Intelligence • SaaS • Enterprise

Arize AI is a company that provides a comprehensive AI observability and evaluation platform designed for AI engineers to build and manage AI applications, particularly those involving large language models (LLMs). The platform offers end-to-end AI tracing, monitoring, and evaluation tools to help users identify and resolve performance bottlenecks, ensure data quality, and improve the performance of AI systems. Arize also supports experimentation and visualization, enabling users to iterate rapidly on AI applications and maintain high-quality service delivery. The company caters to top AI companies, offering solutions for both online and offline LLM evaluation and observability. Arize's tools are particularly valuable for AI model monitoring, troubleshooting, and performance optimization, helping businesses mitigate risks and improve AI outcomes.

📋 Description

• Work closely with some of the most sophisticated ML / GenAI teams in the world. • You will act as a trusted advisor to our customers, while also building relationships with technical and business stakeholders. • Advise on GenAI and ML best practices • Give ML and LLM product demos to technical and business stakeholders • Run strategic business reviews for customers in partnership with our sales team • Interface with our pre-sales engineering team to gather client goals and KPI’s. • Partner with our product and engineering teams to help drive the product roadmap • Spearhead new opportunities within existing accounts to help drive expansions.

🎯 Requirements

• Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production. • Comfortable working in public Cloud environments (AWS, Azure, GCP) • Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn • Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy • Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations • Understanding of GenAI concepts and application evaluation + development lifecycle • Proficiency in a programming language (Python, JS/TS, Java, Go, etc) • Strong Communication Skills - Ability to simplify complex, technical concepts. • A quick and self learner - undaunted by technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV.

🏖️ Benefits

• medical • dental • vision • 401(k) plan • unlimited paid time off • generous parental leave plan • others for mental and wellness support