Engineering Tech Lead

Description

Shield is a global startup, with offices in Tel-Aviv, New-York, London, and Lisbon. 

We’re growing and looking for another important piece of the puzzle. 

Is it you? 

We can’t promise it will be easy, but it is exciting and most importantly – FUN. 

Let’s get down to business.

About the Data Science Group: The Data Science group at Shield is at the forefront of developing and implementing advanced machine learning models and solutions. Our team is composed of talented data scientists, engineers, and subject matter experts who work together to create a high-quality, production-ready surveillance product and services. We are committed to pushing the boundaries of technology and delivering impactful results for our clients.

Position Overview: We are seeking a highly skilled and motivated Engineering Tech Lead to join our Data Science Engineering team. The ideal candidate will have a deep understanding of software development and the ability to guide technical solutions. This role requires a combination of technical expertise, strong problem-solving skills, and the ability to collaborate effectively with cross-functional teams. As an Engineering Tech Lead, you will play a crucial role in exploring and investigating solutions and technologies, contributing to technological and architectural decisions with a hands-on approach.

Key Responsibilities:

• Develop and maintain software infrastructure and solutions to support the efficient development, deployment, and maintenance of machine learning models and our surveillance pipe solution in production.
• Collaborate with data scientists, engineers, and subject matter experts to deliver high-quality, production-ready machine learning models and a fully integrated scalable solution.
• Design and implement software architecture for machine learning solutions.
• Work with containerized environments such as Kubernetes and Docker.
• Utilize AWS for cloud-based machine learning solutions.
• Conduct unit testing and ensure continuous integration and continuous deployment (CI/CD) practices are followed.
• Work in a production environment and closely with data science teams to ensure seamless model deployment and maintenance.
• Stay updated with the latest advancements in machine learning, software development, and related technologies.

Requirements

• Proficiency in software development and the ability to guide technical solutions.
• Ability to explore, investigate solutions and technologies, and contribute to technological and architectural decisions with a hands-on approach.
• Proficiency in Python with 5+ years of Python programming experience – MUST.
• Experience with software architecture design – MUST.
• Strong problem-solving skills with the ability to analyze existing operations.
• Background in Linux and containerized environments such as Kubernetes and Docker – MUST.
• Experience with AWS – MUST.
• Software architecture experience – MUST.
• Experience with tools such as ElasticSearch/OpenSearch, RabbitMQ, Kafka, and Redis.
• Experience with unit testing and CI/CD.
• Experience working in a production environment and with data science teams – Advantage.
• Self-motivated, team player, action and results-oriented.
• Well organized, with excellent communication skills.