The Opportunity
AI is rapidly transforming the world. Whether it’s developing the next generation of human-level intelligence, enhancing voice assistants, or enabling researchers to analyze genetic markers at scale, AI is increasingly integrated into various aspects of our daily lives.
Arize AI is the leading AI observability and evaluation platform, 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, Arize ensures teams have the tools to monitor, troubleshoot, and improve AI in production.
The Team
Our engineering team builds systems that interact with some of the most complex software ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more.
We are looking for a client-obsessed ML Solutions Engineer with entrepreneurial tendencies to join the good fight and help build out our Solutions Engineering org. You’ll be the trusted technical advisors for our customers, driving business value, offering advice, and growing accounts. You’ll accomplish this by leading customers to solutions oftentimes by teaching the product to new users or consulting on best practices. You must be ready for technical discussions with data scientists and engineers, then demonstrate the value of Arize in business discussions with directors and executives. The goal is to enable our customers to become successful and enthusiastic about Arize.
What You’ll Do
- 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.
What We’re Looking For
Note: Even if you do not check every single box, we still encourage you to apply!
- 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.
Bonus Points, But Not Required
- Previous engineering experience in:
- Data Science
- MLOps
- ML Frameworks
- LLM / Agentic frameworks
- Customer facing experience strongly preferred such as Solutions Architect, Implementation Specialist, Sales Engineer, Customer Success Engineer, Consultant, or Professional Service roles
- Prior experience working with applications deployed with Kubernetes
- Prior experience demoing technical products to both business and technical audiences
The estimated annual salary and variable compensation for this role is between $125,000 - $175,000, 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.
More About Arize
Arize’s mission is to make the world’s AI work and work for the people. Our founders came together through a common frustration: investments in AI are growing rapidly across businesses and organizations of all types, yet it is incredibly difficult to understand why a machine learning model behaves the way it does after it is deployed into the real world.
Learn more about Arize in an interview with our founders: https://www.forbes.com/sites/frederickdaso/2020/09/01/arize-ai-helps-us-understand-how-ai-works/#322488d7753c
Diversity & Inclusion @ Arize
Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture
- Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI
- Culturally conscious events such as LGBTQ trivia during pride month
- We have an active Lady Arizers subgroup
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