Senior Software Engineer

Wiliot was founded by the team that invented one of the technologies at the heart of 5G. Their next vision was to develop an IoT sticker, a computing element that can power itself by harvesting radio frequency energy, bringing connectivity and intelligence to everyday products and packaging, things previously disconnect from the IoT. This revolutionary mixture of cloud and semiconductor technology is being used by some of the world’s largest consumer, retail, food and pharmaceutical companies to change the way we make, distribute, sell, use and recycle products.

Our investors include Softbank, Amazon, Alibaba, Verizon, NTT DoCoMo, Qualcomm and PepsiCo.

We are growing fast and need people that want to be part of the journey, commercializing Sensing as a Service and enabling “Intelligence for Everyday Thing”.

We’re looking for a Senior SW Engineer to lead development of algorithmic data processing pipelines at high scale and build the next generation of our data processor.

Requirements:

Experience: 5+ of software engineering experience, of which 2+ years are in data centric projects
Technology experience: Strong proficiency in Flink, k8s.
Cloud Platforms: Solid experience with cloud platforms (AWS, GCP)
Monitoring Tools: Knowledge of monitoring and logging tools as well logging patterns fit for data pipelines.
Teamwork and Communication: Excellent teamwork and communication skills, with the ability to work effectively in a cross-functional team environment.
Self-Learning: High capacity for self-learning to stay updated with the latest in technology practices.
Education: Bachelor's degree in Computer Science, Engineering, or a related field.
Language: Strong spoken and written English skills.

Preferred Skills:

Experience with ML engineering.
Knowledge of data analytics stack: Python, Pandas, Spark
Knowledge of data governance, security, and privacy best practices in data processing
Experience working with coding agents
Global Experience: Experience working in or with global teams is a plus.
Experience with CI/CD tools – GH actions, Argo CD etc

#LI-Hybrid

Responsibilities:

Data Centric Software Development: Lead development of algorithmic data processing pipelines at high scale
Monitoring and Performance Tuning: Optimize resource consumption and monitor performance of complex data pipelines handling high throughput
Collaboration with Data Scientists: Work closely with data scientists and to integrate ML models and other algorithmic artifacts into a production grade data platform and application ecosystem. Facilitate seamless collaboration between teams to ensure ML and data engineering efforts are aligned with business objectives.
Peer collaboartion : Bring knowledge of architecture, design patterns and best practices to help improve quality within the team
Security and Compliance: Ensure the data platform adheres to security best practices and compliance requirements, protecting sensitive data and privacy.
Technology Evaluation and Innovation: Stay abreast of the latest developments in Data processing, ML technologies, and cloud services to drive innovation and adopt new technologies where beneficial.