Interos is the operational resilience company — reinventing how companies manage their supply chains and business relationships — through a breakthrough SaaS platform that uses artificial intelligence to model and transform the ecosystems of complex businesses into a living global map, down to any single supplier, anywhere.
Reducing months of backward-looking manual spreadsheet inputs to instant visualizations with continuous monitoring, the Interos platform helps the world’s companies reduce risk, avoid disruptions, and achieve dramatically superior resilience. Businesses can uncover game-changing opportunities that radically change the way they see, learn and profit from their relationships.
Based in Washington, DC, Interos serves global clients with business-critical, interdependent relationships. The fast-growing private company is led by CEO Jennifer Bisceglie and supported by investors Venrock and Kleiner Perkins. For more information, visit www.interos.ai.
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
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.
- 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 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]