Job Description
1. Designing the technical software architecture that supports Silq's core functions using deep learning and machine learning; Python programming including NumPy, Pandas, and SciPy; data engineering with Python; and version control tools including Git.
2. Designing software in a resilient, scalable, and service-oriented way that will set up Silq for future growth and performance optimization, incorporating computational complexity and complexity analysis for system design using scalable software design and software patterns.
3. Architecting software to introspect the journey of products from design through its conception lifecycle in factories.
4. Modeling complex, real-world supply chain systems by applying data modeling, linear algebra, and probabilistic analysis to information from orders, shipments, inspections, HTS codes, rates, etc., utilizing relational and NoSQL databases including PostgreSQL and MongoDB.
5. Increasing performance optimization and scalability by simplifying workflows through software problem-solving using well-documented and maintainable coding standards, as well as AI-driven automation where applicable.
6. Working with user experience designers to streamline and standardize the daily workflows of the companys Quality Operations Associates in the factories by developing intuitive software solutions and maintainable backend systems using Unix/Linux development, terminal commands, and shell scripting.
7. Interviewing and surveying importers to most efficiently capture their workflow of entering product design and manufacturing information.
8. Using data science techniques, including algorithm development, data modeling, relational database management using MySQL, and Python-based machine learning, to perform risk and uncertainty quantification, predict manufacturing timelines and costs, and display information to clients in an intuitive way.
9. Assisting with the design and implementation of the infrastructure that hosts Silqs software services, using unit testing and debugging techniques to ensure reliability and performance.
10. Running production code using Docker to build scalable and more portable deployable units of software and improve efficiency, optimization, and maintainability.
11. Setting up required computational resources using Kubernetes on Amazon Web Services (AWS) to run server- and client-side modules required to power Silq.
12. Automating document parsing and generation workflows by applying computer vision and applied AI in image and speech recognition.
13. Building system infrastructure to enable auditing of data changes and ensuring sufficient visibility into software using algorithms and data structures and object-oriented programming (OOP).
May telecommute.
This position requires experience with or academic exposure to:
a. Application of linear algebra in engineering domains.
b. Risk and uncertainty quantification in system design and probabilistic methods for engineering analysis.
c. Complexity analysis and computational complexity for system design.
d. Scalable software design; software design patterns; performance optimization; software problem-solving; and code efficiency improvements.
e. Unit testing; debugging techniques; and clean and documented code.
f. Unix/Linux development; terminal commands and shell scripting.
g. Data structures and algorithms; code optimization and maintainability; and object-oriented programming (OOP).
h. Database design and management; relational databases (MySQL, PostgreSQL); NoSQL databases (MongoDB); and Data modeling.
i. Deep learning and machine learning; Python programming (NumPy, Pandas, SciPy); data engineering with Python; version control (Git); and Applied AI in image and speech recognition.
Masters (or foreign educ. equiv.) Degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
$187,750 per annum. 40 hours per week; M-F
Please copy and paste your resume in the email body (do not send attachments, we cannot open them) and email it to candidates at (link removed) with reference in the subject line.
Thank you.