Arize AI is looking to solve the problem of empowering AI engineers to build and deploy high-performing, reliable models as the AI landscape shifts from traditional ML to generative AI and agentic systems.
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
- Understanding of GenAI concepts and application evaluation + development lifecycle
- Proficiency in a programming language (Python, JS/TS, Java, Go, etc)
Responsibilities
- Work closely with sophisticated ML / GenAI teams in the world
- 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 the sales team
- Interface with the pre-sales engineering team to gather client goals and KPI’s
- Partner with the product and engineering teams to help drive the product roadmap
- Spearhead new opportunities within existing accounts to help drive expansions
Other
- 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
- Customer facing experience strongly preferred
- Prior experience working with applications deployed with Kubernetes
- Prior experience demoing technical products to both business and technical audiences
- Estimated annual salary and variable compensation for this role is between $125,000 - $175,000, plus a competitive equity package
- 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
