Founded in 2005 by supply chain risk management expert Jennifer Bisceglie, we have grown into the largest and most influential player in the emerging operational resilience space. This past July we achieved $100 million dollars in Series C funding led by the investment firm Night Dragon, with additional participation from Series A and B investors Kleiner Perkins and Venrock. This latest round of funding brings Interos’ valuation to $1billion, earning us unicorn status.
Based in Arlington, Va., Interos’ breakthrough SaaS platform leverages artificial intelligence and machine learning to model the entire business ecosystems of companies into a living global map. Users can drill down to any single supplier, anywhere – helping businesses and government organizations reduce risk, avoid operational disruptions, and achieve dramatically superior resilience and performance. We have seen hypergrowth in the past 3 years and continue to expand our team across the US and several countries in Europe.
Join us at Interos for a 3 month-long paid apprenticeship, with a goal of graduating to a full-time ML Engineer I role upon successful completion. Work, learn, and grow as part of the Information Extraction team to gather, explore, test, and refine data covering a wide range of topics, from corporate bankruptcy to natural disasters, and build machine learning models to help detect and classify them from news articles. Experiment with state-of-the-art Natural Language Processing (NLP) techniques, build production-ready models, and integrate your work with scalable cloud services. This position is remote-first; we have offices in Arlington, Virginia, but if you live in the United States you are eligible to apply for this position. For the duration of the apprenticeship, your compensation will be $40/hour. This is a temporary, full-time position.
Some of the topics you may learn about through this apprenticeship:
- Deploying scalable NLP applications in a production environment.
- Common NLP tools/libraries/frameworks such as BERT, spaCy, and more.
- Internal tooling for inter-team workflows.
- AWS resources related to gathering data, running models, storing data, and more.
- State-of-the-art NLP techniques during our monthly research paper brown bags.
Applications for the Take-Home are due before the end of 11/22 (any timezone).
Hiring decisions should be made approximately 12/13.
Day 1 for new hires is projected as Jan 3 2022.
Take Home Challenge:
In order to apply for this position you must complete this take-home challenge: Take-Home Challenge. Please submit the challenge as per the document’s instructions. By completing the coding challenge, you will automatically be considered for the position without need for any initial phone screening interviews. Applications for the Take-Home are due before the end of 11/22 (any timezone).
Before completing this take-home, please be aware that only applicants who currently:
- are legally authorized to work in the U.S. and can provide documentation attesting to such status, and
- will not now or in the future require Interos to sponsor an immigration case in order to employ you (for example, H-1B or other employment-based immigration case) This is sometimes called “sponsorship” for an employment-based visa status.
will be considered for this position.
The link to the take-home challenge is hyperlinked on our website so please apply at https://www.interos.ai/job/?id=5616996002.
- Data Collection/Verification/Exploratory Data Analysis.
- Design and develop machine learning models of different types (e.g., Naïve Bayes, Random Forest, deep learning models such as BERT, etc.) from collected data.
- Deploying and monitoring machine learning models in a production environment.
- Iterating upon models given stakeholder feedback/additional data.
- There are no formal education requirements for this position.
- Any hands-on in one or more of the following areas: Machine Learning Models, Natural Language Processing, Text Mining, Information Retrieval, Data Science, Knowledge Engineering, or equivalent experience.
- Familiarity with Python data science/NLP packages, such as pandas, scikit-learn, PyTorch, spaCy, etc.
- Experience with statistical data analysis, experimental design, and hypotheses validation.
- Readiness to collaborate with engineering teams to develop prototypes and software product.
Stuff That Really Impresses Us:
- Formal education or professional experience in Computer Science, Data Science, or Computational Linguistics.
- Contributions to open-source projects in the NLP/NLU space.
- Good experience creating entity, relationship, and event extraction models.
- Great sense of humor.
- Positive, good-natured, and generally pleasant to be around.
- Demonstrated commitment to building a diverse and inclusive culture.
- A sense of adventure.
Interos is required to comply with Federal Executive Order 14042 mandating employees be vaccinated against COVID-19. Accordingly, as of January 4, 2022, all Interos employees must be fully vaccinated* against COVID-19, unless you have a legally valid medical or religious reason. Any requests for exemptions based on medical or sincerely held religious beliefs will be evaluated confidentially by our Chief People Officer after hiring.
*Fully vaccinated means an individual must have received their second dose of the Moderna or Pfizer vaccine or the single dose of the Johnson & Johnson vaccine no later than 14 days before January 4, 2022.
Interos is proud to be an Equal Opportunity Employer and will consider all qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity, genetic information, national origin, disability, protected veteran status or any other classification protected by law.
If you are a candidate in need of assistance or an accommodation in the application process, please contact [email protected]