Indico is seeking a Field Engineer to help make our customers successful with our Intelligent Process Automation product. You’ll work directly with the CTO to make sure that our product is anticipating customer needs, and develop custom integrations and tooling to close the gap where it’s not. A big part of this role is learning. We don’t assume that applicants will be able to execute in this role from day one, the first several months will be spent learning the basics of modern machine learning and development in a modern python stack.
- Work directly with the CTO to create realistic execution plans for Customer projects ranging from 1-2 weeks to 3-4 months
- Develop ETL tooling and custom integrations to seamlessly work with customer data where needed.
- Work with customer subject matter experts (SMEs) to deconstruct use cases into tractable machine learning problems
- Label small amounts of data to demonstrate product functionality to SMEs and other business users.
- Think critically about new ways to visualize data and make the machine learning process more relatable to end users
- Provide feedback to product management and marketing as we find gaps in existing product capabilities
- Self-directed and active learner
- Communication-focused, comfortable giving regular updates to stakeholders
- Comfort with basic ETL and data science processes (Pandas + sklearn)
- Comfort building simple backend servers (Python + Tornado)
- Deep desire to connect with users and help make machine learning a more accessible technology
- Experience and desire to work with non-technical users to help them understand various aspects of technology
- Travel 10% - 20% of the time, meeting with clients in Boston and NYC on occasion
- Experience in the field of machine learning
- Comfortable with public speaking and presentation skills
- Comfortable leading a small scale user-centric product development process
- Comfort building basic UIs (React + Redux)
- 3+ years experience in industry
Indico is a venture-backed startup making the application of deep learning practical in the enterprise. Our focus is on helping to automate tedious back-office tasks, and improve the efficiency of labor-intensive document-based workflows. The fundamental branch of technology we use to achieve this is known as transfer learning, which allows us to train machine learning models with orders of magnitude less data than is required by traditional techniques, with a strong emphasis on NLP and text processing.