Software Engineer, Infrastructure

At Milestone, your work goes beyond what the human eye can see. With our unique video technology software, you help people make wiser and more responsible decisions – in and beyond security. Whether you advance our software, inspire to new integrations, or elevate our customers, you are part of a growth company recognized by the industry. We have a unique people-first approach to everything we do, and it’s not just empty words. Being part of a fun, friendly, and flexible environment you’ll find, that working here almost feels like a home away from home. If you are curious to know more about who we are, we suggest you visit http://milestonesys.com/career 

You will be part of a team that defines and implements the standards of Briefcam's data infrastructure and data automation methods, from data collection, through MLOps pipelines, to models' accuracy monitoring. You will work alongside researchers in the field of Computer Vision for video analytics and act as a key enabler of our Deep Learning research.

Responsibilities:

• Learn, use, optimize, and develop advanced MLOps technologies, distributed systems, Docker, Jenkins, etc.
• Support the process of annotated data generation for training and testing AI models including development of algorithms for pre-processing videos, semi-automatic annotation, and generation of synthetic data
• Participate in defining the way our data is stored, consumed, manipulated, integrated, and managed as part of the deep learning R&D process
• Develop end-to-end evaluation procedures for new algorithmic features and integrate them with CI/CD tools for constant monitoring
• Develop various tools for supporting the research team 
• Identify and evaluate new and emerging technologies that may drive improved efficiency and value to the data-driven algorithms developed by the research team

• +5 years of software development experience
• B.Sc. in Computer Science / Software Engineering or similar
• Proficient in Python
• Knowledge of Linux operating systems
• Proven ability to communicate and work with multiple stakeholders
• Experience as a data/MLOps engineer – major advantage
• Knowledge of Computer Vision and Deep Learning – advantage
• Hands-on experience with Continuous Integration (CI) and/or QA automation with Jenkins or similar – advantage
• Experience with visualization and analytical tools – advantage
• Experience in designing and managing data annotation operations - advantage