Sr. Machine Learning Engineer Vodafone

Develop solutions for real world, large scale problems.
Design, develop, test, deploy, maintain and improve software.
Design, develop, and operate the data pipeline platform.
Manage individual project priorities, deadlines and deliverables.
Create /Design and maintain ML pipeline and workflows.
Refactor and optimize ML algorithms to fit on the final solutions.
Create /Design and maintain automation workflows.
Understand the product in detail, empathize with customers, so you can predict potential issues in feature development.
Develop and deploy integrations/APIs on cloud.
Deliver dockarized micro services on TTD approach.
Facilitate the cloud capabilities within the developed tools.
Create /Design Web applications and tools that help data scientists to do their work effectively.
Create /Design Web applications and tools that allow customers to consume our ML services.
Follow best practices and standards for accessibility and cross-browser compatibility
Stick to established coding standards and group procedures individually and in teams
Add to engineering team s culture of high code quality
Design and build UIs on any server platform in a team environment
Manage activities, scope and timelines on the projects with minimum supervision.
Work with planners to design, develop, and operate tools that fulfill internal requirements.
Provide user support.
Work with other teams to conduct troubleshooting when necessary.
Mentor interns and junior developers, and interview engineering talent.
Code review and peer programming

Strong fundamental knowledge of computer science, such as data structure, algorithm design, and computational analysis
Experience with one or more general purpose programming languages including but not limited to: Java, Python, JavaScript, or Go.
Experience with Information Retrieval techniques and frameworks.
Proficiency in HTML, Javascript, CSS and general Web 2.0 techniques.
Experience taking a leading role in building complex software systems that have been successfully delivered to customers
Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
Experience with Cloud technologies like GCP and/or AWS products.
Experience with Django/ Flask.
Experience with react js.
Experience RESTful API, SOAP, graph...etc.
Experience containerization technologies like docker and kubernetes.
Experience with concurrent/multi-threaded programming.
Experience with development and system operation in Linux/Unix environments.
Hands-on Experience with Machine Learning and it's libraries like Sklearn.
Python Data Science stack (NLTK, Pandas, Numpy).
Data Mining, Natural language Programming.
Familiar with deep learning pipelines and tensorflow basics.
Familiar with big data platforms like Hadoop, Spark.