ML Solutions Engineer
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 learned systems in some way.
Arize is the leading machine learning observability platform to help ML teams discover issues, diagnose problems, and improve the results of machine learning models. In short: we are here to build world class software that helps make AI work better.
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
- You will act as a trusted advisor to our customers, while also building relationships with technical stakeholders
- You will act as the “Voice of the Customer” - Regularly engaging them on status calls, educating on product roadmap and QBRs, managing escalations, while influencing our roadmap in partnership with our Product team.
- Interface with our pre-sales engineering team to gather client goals and KPI’s.
- Spearhead new opportunities in which Arize can provide the most value that will drive renewals and new accounts.
What We’re Looking For
- Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models in production.
- Comfortable with Kubernetes and public Cloud environments (AWS, Azure, GCP)
- Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn
- 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
- Proficiency in a programming language (Python, R, 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
- ML Frameworks
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