Who are we?
Verta is an MIT and Twitter spin-off building Machine Learning Operations software enabling enterprise data science and machine learning teams to build and ship more intelligent products. Verta’s mission is to bring order to the chaos of machine learning and data science workflows and to enable teams to rapidly and reliably build and operate machine learning models. Verta’s technology is based on ModelDB, a state-of-the-art model management system developed at MIT CSAIL and hardened at Twitter by the Verta founding team.
Verta works with forward-thinking AI and ML teams including the leading worldwide workplace productivity application, leading chip manufacturer, and several AI-first companies to enable them in building more intelligent products.
At Verta, we are building a suite of products targeted at expert data science and ML engineers, practitioners who frequently work across a whole ecosystem of data, software, and modeling tools. Our goal is to build elegant solutions that bring order to the chaos of ML tools and help data science teams to build and ship more intelligent products.
Towards this mission, we are looking for a Data Science intern to help launch some of our key initiatives.
Apply if you are looking to (a) work in a fast-paced environment with rapid product iteration; (b) collaborate with an exceptional engineering and data science team; (c) aren’t afraid to break new ground every day; (d) are a results-oriented data science-evangelist!
What you’ll do
- Partner with a team of highly motivated and smart engineers & data scientists to launch key product features in model management, model deployment, monitoring, and explainability
- Build and ship models & end to end demos for a variety of ML use cases to help our customers realize the value of the Verta MLOps platform
- Be a DS/ML evangelist for best practices via blogs, code samples, and tutorials
- Enrolled in an undergraduate or in a graduate program, preferably in a science or quantitative field
- Hands-on experience with applying quantitative approaches, analyzing and interpreting data
- Ability to work independently on open-ended projects
- Solid understanding of statistical concepts and machine learning models
- Proficient in one or more programming languages such as Python (must have), Scala, R.
- Comfortable collaborating with cross-functional teams using strong written and verbal communication skills