Python Software Engineer 1058 views

Role Responsibilities 

• Hands-on design, development, and support of world-class production Python solutions, both web application, and machine learning. Contribution to standards about production-quality engineering and QA for Python solutions. Active pull request participation, branch management, other code reviews of other Python developer’s work, etc.
• Working with their DevOps team for production Machine Learning AI solutions (DevOps for machine learning is a new area for the industry, with little current conventional best practice, Streetbees expertise in ML creates a real opportunity to do leading-edge DevOps work production rising that). Working with the other engineers to define how Python software engineering should be done
• Development and support of data engineering platform, Python web applications and APIs, and machine learning platforms, all on AWS including using specialist ML accelerators
• Being an active part of the group of engineers reviewing and making key tech design decisions, and coordinating work and operations
• Keeping up to date with the latest evolutions in Python software engineering best practice and technologies

Skills and Experience 

• Excellent Python knowledge and skills relative to the level of experience, including both Python language technicalities, and the technical underpinnings of the Python platform, in particular including maintainability, performance, and reliability
• Years of commercial experience building and supporting large scale web, app and API platforms with Python relative to experience
• Experienced with the AWS application suite (bonus points if you have experience with DevOps technologies around it such as Docker, Kubernetes, and Terraform)
• Experienced with relational, but also NoSQL, databases (bonus points for Postgres specifically). The more knowledge of data processing, vectorization, and machine learning frameworks the better.
• Experience with requirements specification, Python testing tools, with software design patterns, with Agile development processes

Additional Information

• Streetbees is a tech start-up that is transforming how companies can gain insights into the markets for their products, to make better products that better provide for the needs of their customers. They are using machine learning and software engineering to create faster, lower cost, higher quality, and more automated ways to gather information from people around the world, and to understand the patterns, trends, and opinions.
• Streetbees has a very strong engineering team and platform, combining the best in machine learning, data management pipelines, web platforms, and mobile apps. They work with Python for their data science and machine learning, Ruby and Elixir with ReactJS for their web apps and APIs and middleware, and Swift and Kotlin (their Android codebase is 100% Kotlin). Everything is entirely hosted in AWS, all repos in Github, everything containerized.
• An opportunity exists for a Python Software Engineer to join their team, particularly those who have the enthusiasm to work at the intersection of scalable distributed web platforms with data engineering and machine learning technologies. This is the core of Streetbees technology activities as a leading ‘applied AI’ company – it is one of the most exciting frontiers of modern technology, where new types of software are emerging, and new capabilities that were simply not possible a few years ago are now being created. They are looking for an enthusiast to contribute to building something truly great in this space.
• The Python Software Engineer will have strong technical and software engineering knowledge relative to their years of experience, so that they are able to make a major contribution to creating production-quality AI solutions. They are looking for engineers at both mid and senior experience levels as they are more driven by a colleague’s contribution and skills than the length of service, and as a fast-growing start-up, they have flexibility in exact skills requirements in order to build the best team. Successful candidates will probably have either significant data engineering (e.g. PySpark, Airflow, Pandas, etc), or web app engineering (e.g. Django, Flask, etc) backgrounds, or another background where Python is a leading tool for engineering purposes.
• This is a fully hands-on position. Any experience with machine learning engineering using Tensorflow, Keras, and PyTorch would be a large advantage but is not required if someone has strong Python software engineering knowledge in another of the common Python use cases (e.g. web development and data engineering). This is not a role for a pure data engineer or data scientist though, it is a software engineering role and would particularly suit engineers who have significant experience outside of machine learning and self-motivated interest in developing expertise in machine learning engineering, as a means to produce the new generations of software capability now possible by combining machine learning aspects with established engineering approaches.