Tulip, the Frontline Operations Platform, is empowering the worlds leading manufacturers to improve the productivity of their teams, the quality of their output, and the efficiency of their operations. With Tulips no-code platform, manufacturers can empower those closest to operations to digitally transform their facilities and gain real-time visibility into the people, machines and processes involved in production--all in a matter of days.
Manufacturers of all sizes, across industries including consumer electronics, aerospace and defense, contract manufacturing, automotive, apparel, medical devices and more, have implemented Tulips intuitive platform to solve some of the most pressing challenges in manufacturing: error-proofing processes with guided workflows, integrating industrial IoT (IIoT) technologies with legacy factory machines, and capturing and analyzing real-time production floor data.
A spinoff out of MIT, the company is headquartered in Somerville, MA, with offices in the UK and Germany. It has been recognized as a MES Challenger on the Gartner Magic Quadrant, Frost and Sullivan Entrepreneurial Company of the year and a World Economic Forum Technology Pioneer. You can learn more and get started for free at Tulip.co.
Data is always on your mind. How to collect it, how to index it and how to draw conclusions from it. Its called data Science for a reason! Big disorganized data doesnt intimidate you, it draws you to take a closer look, open a notebook and clean it up.
Youre a recent advanced degree graduate or an experienced engineer, with the background and skills to extract insights from messy data and make it into a must-have product for your clients, be they internal or external.
You have a solid background in data engineering and machine learning mechanics. You know firsthand how to clean up data, build pipelines, train models, evaluate them and ship data products on an edge-cloud hybrid platform to thousands of shop floors worldwide.
What skills do I need?
- Education: B.S in a computational science (computer science or engineering, applied mathematics, statistics or related field) with 3+ years of experience in computer vision, or an advanced degree (M.S, PhD) in a computational domain with 1+ years of experience (internships welcome).
- Specialization in a machine learning domain: data science, computer vision, signal processing, informatics.
- Demonstrated software engineering skills, such as programming patterns, algorithms, software development cycles, cross-OS building environments.
- Demonstrated engineering skills in Machine Learning, such as constructing and training deep models, data cleaning and augmentation, time-series data analysis, feature extraction and backbones, a broad knowledge of ML algorithms and their tradeoffs, etc. Preference for published or publicly available work.
- Solid knowledge of applied mathematics for machine learning, such as Linear Algebra, Multivariate Calculus, Statistics, Sampling theorems, Algorithmics and Informatics.
- Good written and conversational skills.
- Build, code, test, and maintain high quality software
- Develop, maintain, and test machine learning algorithms
- Develop and ship machine learning features on the Tulip platform
- Work with clients to implement machine learning on their shop floor
- Contributes code across the engineering groups
- Advance the agenda of machine learning and demonstrate its impact on the companys business
- Chief Technology Officer
- Lead Scientist and Tulip Labs personnel
- Head of Engineering
- Lead Data Engineer
- Lead Edge Engineer
- Lead Hardware Engineer
Working At Tulip
We are building a strong, diverse team that values hard work, families, and personal well being.
We are an equal opportunity employer and building a diverse team is our top priority. At Tulip, we celebrate all. Qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Help us build an inclusive community that will transform manufacturing.