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.
The Junior ML Engineer is a core member of the agile teams facilitating trained ML models to deliver E2E solutions as a final product that fulfill the COE automation target. The junior 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.
- Develop solutions for real world, large scale problems.
- Design, develop, test, deploy, maintain and improve software.
- Manage individual project priorities, deadlines and deliverables.
- Create and maintain ML pipeline and workflows.
Develop and deploy integrations/APIs on cloud.
- Bachelor Degree in computer science and/or engineering or equivalent with 0-3 years of relevant experience.
- Working in international, distributed teams.
- Experience of working on projects that span multi-disciplinary areas of differing size and complexity to meet business expectations and deliver results
- Confident and able to liaise and influence at all levels within Vodafone and/or relevant customer organizations
Able to communicate effectively across organizational, technical and political boundaries, understanding the context
- Computer Science fundamentals in object-oriented design, data structures, algorithms and complexity analysis.
- Proficiency in Python.
- Information Retrieval.
- Data Mining.
- Natural language Programming.
- Machine Learning
- Python Data Science stack (NLTK, Pandas, Numpy).
- 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 GCP and/or AWS products.
- Hands-on Experience with Sklearn, Tensor Flow.
- Experience with Django/ Flask.
- Familiarity with react js.
- RESTful API.
- Familiarity with docker and kubernetes.
