The Opportunity

AI is rapidly changing the world. From processing job applications and credit decisions to making content recommendations and helping researchers analyze genetic markers at scale, many aspects of our daily lives are touched by machine learning systems in some way. 

Arize is a leading machine learning observability platform that helps ML teams discover issues, diagnose problems, and improve the results of machine learning models. In short, we are here to build world-class open-source software that empowers AI practitioners and streamlines ML operations workflows.

The Team

Our Open-Source Engineering team develops and maintains the open-source libraries and tools that powers Arize and Arize-Phoenix, an ML Observability platform that runs in a python notebook. We leverage technologies such as Starlette, GraphQL, Pandas, and UMAP to provide a powerful EDA and fine-tuning workflow within a Python notebook. As part of this team, you'll have the opportunity to contribute to cutting-edge open-source projects and shape the future of ML and LLM development

You will have a significant impact on the success of our company in this highly technical space. You'll not only contribute to projects but also help shape the team's culture, structure, and practices as we scale.

What You’ll Do

• Develop and maintain a high-quality open-source Python package that is a key part of Arize's ML observability offering.
• Write clean, efficient, and maintainable Python code that scales with increasing data volume and user demands.
• Design and build APIs specific to ML workflows, ensuring seamless integration with popular Python-based ML frameworks.
• Leverage large language models and model outputs such as embeddings to build novel troubleshooting workflows.
• Utilize techniques such as UMAP and HDBSCAN to create powerful visualizations for embeddings.
• Collaborate with the product, design, marketing, and frontend engineering teams to enhance the adoption of Arize’s open-source tools.
• Prototype, optimize, and maintain packages and notebooks that educate and evangelize Arize’s tooling.
• Contribute back to the open-source community by actively participating in code reviews, issue tracking, bug triaging, and documentation.
• Stay up to date with the latest advancements in ML ops, Python libraries, large language models, and troubleshooting techniques.

What We’re Looking For

• Adaptability and Positivity: This is an incredibly dynamic field and requirements will change frequently. A positive mindset and adaptability to needs is a must.
• Exceptional Python Skills: We are looking for individuals with significant experience in Python programming, coupled with a proven track record of maintaining and optimizing Python packages. An understanding of Python's best practices is essential.
• Experience with data science packages, particularly Pandas. Knowledge of and experience with other tools in the data science ecosystem would be an added advantage. This will be critical in dealing with the data-centric aspects of our work.

Bonus Points, But Not Required

• Experience in building and maintaining open-source software packages.
• Experience with large language models and troubleshooting embeddings.
• Working knowledge of machine learning and data science principles.
• Contributions to relevant open-source projects or active involvement in the Python community.

The estimated annual salary for this role is between $100,000 - $185,000, 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.

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