Sr. Machine Learning Engineer

Join Us

At Vodafone, we’re not just shaping the future of connectivity for our customers – we’re shaping the future for everyone who joins our team. When you work with us, you’re part of a global mission to connect people, solve complex challenges, and create a sustainable and more inclusive world. If you want to grow your career whilst finding the perfect balance between work and life, Vodafone offers the opportunities to help you belong and make a real impact.

Role purpose:

The senior ML Engineer is a core member of the agile teams facilitating trained ML models to design and deliver E2E solutions as a final product that fulfill the COE automation target. The senior machine Learning Engineer job is to mainly develop and design machine learning pipeline / integrations using different machine learning platforms and his software engineering / cloud skills. Ability to prioritize well, communicate clearly, have a consistent track record of delivery and excellent software engineering skills. Creative engineering balanced with high quality and a customer focus. Must be able to work across multiple facets of the project and juggle multiple responsibilities at the same time. Strong analytic capability and the ability to create innovative solutions.

Key accountabilities and decision ownership:

• 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.

Core competencies, knowledge and experience:

• 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.
• Have a high preference to work on data engine, but also have a good understanding of how the services layer works, and how data is consumed by the front-end.

Must have technical / professional qualifications:

#VOIS #BeUnrivalled #Createthefuture