Key skills
GoGraphQLTypeScriptReactData VisualizationGeospatial DataTime-Series DataComputer VisionBig Data AnalyticsLogistics KnowledgeCommunication SkillsCollaboration SkillsProblem-Solving SkillsGrowth MindsetTeam PlayerMLData WarehousingAnalyticscargoCommunicationCollaborationCustomer Success
About this role
Samsara is the pioneer of the Connected Operations™ Cloud, enabling organizations to harness IoT data for improved operations. In this role, you will develop critical product lines for Smart Trailers, focusing on building intelligent systems to enhance logistics and asset utilization while ensuring cargo safety and compliance.
Responsibilities:
- Bring a customer-focused mindset to all development, balancing the need to iterate quickly and deliver customer wins iteratively
- Partner with the Engineering Manager to advocate for long-term technical health of our products alongside product priorities
- Act as a force multiplier on the team by leveraging other engineers and personally exemplify how to deliver value at Samsara
- Mentor other engineers by actively participating in design and implementation conversations across the team
- Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices
Requirements:
- Bachelor's Degree in Computer Science/Engineering or equivalent practical experience
- 8+ years of relevant industry experience in software development
- Strong programming/coding fundamentals with proficiency in at least one of the following: Go, GraphQL, TypeScript, React
- Excellent communication, collaboration, and problem-solving skills, with a demonstrated ability to manage technical discussions
- Data Visualization Skills: Experience building frontend interfaces that make complex data (utilization rates, equipment status) digestible and actionable for users
- Geospatial & Time-Series Data Experience: Proven ability to work with map-based data (geofences, lat/long coordinates) and time-series sensor data
- Experience with Computer Vision/ML Integration: While you don't need to be an ML Engineer, you have experience consuming ML model outputs (e.g., from camera feeds) and integrating them into user-facing applications
- Big Data Analytics: Familiarity with data warehousing or processing frameworks to derive insights from trillions of data points
- Logistics or Supply Chain Domain Knowledge: Understanding of concepts like cargo compliance, yard management, or freight workflows
- Zero-to-One Mindset: Experience building and shipping a product from scratch and scaling it for growth and business impact