RADAR

Machine Learning Engineer

• Build and scale ML infrastructure: Design and maintain scalable, reliable and efficient production pipelines for feature engineering, training, prediction and model serving using tools including Airflow, Big Query and Kubeflow
• Drive model performance: Train, validate and deploy high-quality ML models, applying advanced techniques in feature selection, hyperparameter tuning and model architecture choices to improve the accuracy of our products
• Accelerate ML development: Optimize feature engineering pipelines for performance and scalability while collaborating with Data Science to research, develop, and deploy new features that improve model accuracy
• Ensure reliability: Implement comprehensive model monitoring, automated training pipelines, and observability solutions to maintain model health and performance
• Champion best practices: Apply CI/CD principles including automated testing, model validation, and deployment strategies

Data Analyst

• This role leads the optimization and post-go-live integration of RADAR’s platform across pilot and fleet deployments.
• You will act as the main liaison between RADAR’s engineering organization and retail customers, ensuring ongoing success and scale of the solution.
• You will collaborate cross-functionally to surface performance issues, quantify performance, and implement improvements to maximize value for the customer.
• Complete onboarding with Customer Solutions, Engineering, and Customer Experience teams.
• Review RADAR’s solution architecture and integrations with fleet and pilot customers.
• Analyze current QA and monitoring to identify key improvement opportunities.
• Conduct stakeholder interviews to document known pain points.
• Shadow current engagements to understand the flow of feedback, escalation and remediation.
• Design and validate QA scenarios for field testing during and after deployment of new features and customers.
• Collaborate with engineering and Customer Experience to support field testing.
• Collaborate with engineering and product to triage known and new performance issues.
• Contribute to cross-functional workshops focused on customer success.
• Drive iteration on solution components based on system performance and customer feedback.
• Create baseline dashboards to visualize key health and performance metrics.
• Formalize a playbook for system issue detection and remediation.
• Begin mentoring newer team members on performance troubleshooting and analysis.

Senior Data Analyst, Customer Solutions

Support Engineer

• Partner with IT Engineering Teams and other departments to deep-dive and find root causes for customer and deployment issues
• Drive tasks, projects and issues to timely resolution for external and internal customers
• Support RADAR’s employee onboarding/off-boarding process
• Work with external vendors to schedule maintenance dispatches and minimize customer impact
• Provide support to customers through Jira and other ticketing tools and communicate resolutions
• Collaborate with engineering to escalate issues and produce reports for customers and stakeholders
• Participate in on-call rotation and adhere to SLA agreements
• Manage dispatch process including scheduling with vendors and customers
• Collaborate with Hardware team to ensure RMA equipment is received and tested
• Resolve complex problems by referring to related tickets and documentation
• Create and edit documentation and runbooks for troubleshooting
• Use monitoring tools and analyze appliance logs
• Identify and automate processes in Jira to increase efficiency

Store Technical Support Specialist

Analytics Engineer

• At RADAR, we're transforming the way the world thinks about physical retail.
• Our platform combines RFID and AI to unlock hyper-accurate product visibility and automation at scale.
• Design, build, and maintain scalable, reliable, and efficient data pipelines using Apache Airflow & Beam.
• Ensure pipelines are robust and maintain high levels of trust and integrity by implementing data quality checks, unit tests, pipeline monitoring, error handling, and logging mechanisms.
• Design and build the data model to support scalable and repeatable analytics.
• Collaborate with Data Science, Engineering and Product teams to understand data needs and translate into solutions.
• Write and optimize complex SQL queries including use of CTEs and window functions.
• Develop RADAR’s data product offering.
• Develop custom visualizations and dashboards with tools like Looker.

Customer Support

• Provide remote technical support during live deployments of RADAR systems to our retail customers and vendor partners.
• Troubleshoot hardware, software, and connectivity issues while ensuring a seamless installation experience.
• This position is primarily overnight.
• Learn RADAR's deployment process and Runbooks; interact with Zendesk and internal dashboards.

Machine Learning Engineer

Senior Data Analyst, Customer Solutions

Store Technical Support Specialist

Analytics Engineer

Deployment Tech Support Specialist