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Required LOW LEVEL ENGINEER 
What youll be doing
Full project ownership for critical parts of the core products; design and specification, implementation, communication, test plans and delivery.
Develop and maintain the main logic and capability that is running directly on the IOT edge devices.
Liaise with colleagues in engineering, product managers to help prioritize features and define the product roadmap.
Uphold engineering best practices applied across projects and teams.
Mentor and level up fellow teammates with pairing and code reviews.

We are growing and are looking for a Senior iOS Engineer to join our mission in developing life saving software!
About the role:
You'll play a crucial role in shaping and evolving the foundation of our product, overseeing the entire process from designing to implementing a sophisticated iOS native application. Collaboration is key as you'll work closely with diverse teams, including backend engineers, product managers, data analysts, and UX designers, to deliver innovative features that meet the highest standards using the latest technologies available.
You will:
Develop high-quality iOS applications, focusing on performance, scalability, and maintainability.
Collaborate with cross-functional teams to define, design, and ship new features.
Write clean, efficient, and maintainable code following best practices and design patterns.
Conduct code reviews to ensure code quality and adherence to coding standards.
Mentor developers and contribute to their professional growth.
Stay updated with the latest trends and technologies in the iOS ecosystem.
Work closely with UI/UX designers to implement pixel-perfect designs.
Troubleshoot and debug issues, providing timely resolutions.
Participate in architectural discussions and propose innovative solutions.

We are looking for an experienced software Engineer to join our AI group and build our next generation Machine learning infrastructure and enable the research and development of new models.
What will you do?
Work closely with data scientists, data engineers and other stakeholders to streamline, implement and optimize our machine learning models and data pipeline infrastructure.
Design and build automated pipelines and tools for model training, testing, validation, and deployment to ensure smooth and efficient operations.
Manage infrastructure requirements for machine learning projects, including cloud resources, container orchestration (e.g., Kubernetes), and distributed computing systems.
Build and maintain monitoring and alerting systems to proactively identify the models performance and bottlenecks and optimize the systems speed, scalability, and cost.

Lead the design, implementation, and ongoing management of our company's data pipeline architecture.
Lead team architectural discussions
Manage a team of 2-3 data engineers
Work as an integral part of the data team and work closely with data Scientists, data Analysts and data Engineers.
Work directly with others (Developers, Product, and Internal stakeholders) to develop a solid understanding of the business application and requirements for which the application is being designed.