Fullstack Software Engineer
On-site · Ecublens, Vaud, Switzerland
Job Summary
Full-stack Software Engineer to design, plan, and develop new customer-centric features for Wireless cloud solutions in a fast-paced, multi-cloud environment. Role involves developing and maintaining wireless products and software services that connect devices to enterprise networks, designing and implementing full-stack features across front-end, cloud-backend, and AI/ML components, collaborating on data-driven features, end-to-end testing in simulated and real hardware, and supporting continuous integration and automated testing systems.
Required Qualifications
- Experience in building rich web UIs with React and Redux, or similar frameworks
- Experience with web backend technologies such as Ruby on Rails, Python, or Scala
- Familiarity with data engineering, ML model lifecycle management, and deployment techniques
- Familiarity with designing and implementing features using relational databases
- Strong problem-solving skills, testing, troubleshooting, and debugging experience
- Adaptable, proactive, and willing to take ownership
- Strong collaborative and interpersonal skills
- Preferred: Cloud development knowledge, AI/ML workflows, modern data streaming/processing tools, Kubernetes, Docker, and AWS/Azure
Desired Qualifications
- Experience building rich web UIs with React and Redux or similar frameworks
- Backend experience with Ruby on Rails, Python, or Scala
- Familiarity with data engineering, ML model lifecycle management, and deployment techniques
- Familiarity with relational databases
- Strong problem-solving, testing, troubleshooting, and debugging skills
- Adaptable, proactive, willing to take ownership
- Strong collaborative and interpersonal skills
- Solid understanding of cloud development and technologies
- Experience with AI/ML workflows including data ingestion, preprocessing, model training, validation, deployment, and monitoring
- Knowledge of networking protocols
- Experience thriving in a collaborative, agile environment with multi-functional teams
- Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn)
- Familiarity with data streaming, analytics, and processing tools (Kafka, Spark, Databricks, Snowflake)
- Cloud infrastructure expertise (AWS, Azure), Kubernetes, and Docker
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