Python Developer

Background Quantitative risk assessment is a fundamental action to ensure safe operation of critical high-tech systems. The increased constraints imposed by international standards together with the ever-growing penetration of AI components in high-tech systems make rigorous and powerful risk assessment more important than ever. Various techniques have been developed throughout the years to analyze the safety and reliability of systems. One of the most relevant is Fault Tree Analysis (FTA). Every day, millions of engineers are using fault trees to model their systems and analyze the probability of failures. FTA is applied to many safety-critical systems and their use is required for instance by the Federal Aviation Authority (FAA) and the Nuclear Regulatory Commission (NRC) USA, in ISO 26262 for autonomous driving or for software development in aerospace systems (by NASA and ESA). While fault trees are easy to understand and thus, widely used, their modelling capabilities are severely limited. This lack of flexibility hinders accurate and precise modelling of real-life systems e.g., self-driving cars, hyperloops and drones.. To overcome these drawbacks, several extensions of fault trees have been proposed in the last decades. Dynamic fault trees (DFT) are a prominent extension of fault trees overcoming these limitations. DFTs have been co-developed by NASA Formal Methods group to model more complex behaviors and dependability patterns. While fault tree models represent how failures occur at system component level and how they propagate through sub-systems, eventually leading to system level failures, their analysis focuses on computing various dependability metrics, i.e. key performance indicators that measure how well a system performs. Standard metrics are the system reliability (i.e. the probability that no failure occurred until time T), the availability (i.e. the average percentage of time that a system is operational), the mean time to failure, the mean time between failures, the criticality of components (i.e. to what extent does a component failure contribute to a system failure) etc. Various extensions include the cost and impact of failures.

Opportunity We at DGB Technologies, in collaboration with MOVES group at RWTH Aachen University Germany and FMT group at Twente University The Netherlands, are building tools for the modeling and quantitative analysis of real-life high-tech systems based on probabilistic model-checking techniques. If you are willing to work on cutting edge technologies and have experience in tool building used in performance, reliability and safety analysis of complex systems, this is a right opportunity for.

We are looking for a Python Web Developer responsible for managing the interchange of data between the server and the users. Your primary focus will be the development of all server-side logic, ensuring high performance and responsiveness to requests from the front-end. You will also be responsible for integrating the front-end elements built by your co-workers into the application; therefore, a basic understanding of front-end technologies is necessary as well.

Job Responsibilities

• Writing reusable, testable, and efficient Python code.
• Coordinating with development teams to determine application requirements.
• Design and implementation of low-latency, high-availability, and performant applications.
• Integration of user-facing elements developed by front-end developers with server side logic.
• Assessing and prioritizing client feature requests.
• Implementation of security and data protection.
• Producing detailed design documentation.

Required Skill Set

• 1-2 years of experience as a Python developer.
• Expert in Python, with knowledge of at least one Python web framework (Django or Flask).
• Able to integrate multiple data sources and databases into one system.
• Understanding of the threading limitations of Python, and multi-process architecture.
• Basic understanding of front-end technologies, such as JavaScript,TypeScript, Angular, HTML5, and CSS3.
• Understanding of fundamental design principles behind a scalable application.
• Familiarity with event-driven and socket programming in Python.
• Able to create database schemas that represent and support business processes.
• Strong unit test and debugging skills.
• Proficient understanding of code versioning tools such as Git.
• Ability to collaborate on projects and work independently when required.
• Familiarity with virtualization tools like Docker and containers.
• Must have knowledge of Compiler Construction things, Lexical Analyzer, Context Free Grammar (CFG), Parser and Translators.

Preferred Additional Skills

• Exceptional communications skills – written and verbal
• Publishing record in Deep/machine/reinforcement learning, security, software architecture and have strong tie-up/network with experts/academics/researcher.
• Team player and great collaborator.
• Experience working with an international team spread across geography.

To Apply

Send your resume at contact@dgbtek.com