Senior Software Engineer - Safety Detection Precision
On-siteLondon, England, United Kingdom
Job Summary
Build and evolve core systems that review safety detections, intelligently identify ambiguous cases, and automate triage to improve detection precision. Partner with product, design, AI, and ML infra to turn real-world review outcomes into better model feedback loops and higher-quality safety detections. Own complex projects end-to-end, from technical design through rollout, measurement, and iteration in production. Use modern AI-assisted engineering workflows to accelerate prototyping, debugging, and iteration while maintaining strong engineering judgment and code quality. Raise the bar for quality, operability, and engineering clarity across Samsara's Safety platform.
Required Qualifications
- 4+ years of software development experience, primarily in backend or distributed systems
- Experience on a product engineering team shipping systems that solve real customer problems
- Demonstrable focus on customer experience, with the ability to connect technical decisions to customer value
- AI-first engineer who consistently uses modern AI coding and reasoning tools to improve engineering efficiency, accelerate delivery, and raise the quality of codebases, while applying strong judgment to validate outputs and maintain a high bar for correctness, maintainability, and reliability
- Strong programming and software engineering fundamentals, with experience building production systems in at least one modern programming language
- Experience designing and building large-scale, high-throughput systems
- Experience operating in a data led and data backed environment
- Strong cross-team and cross-functional communication, collaboration, and problem-solving skills, with the ability to lead technical discussions clearly and constructively
Desired Qualifications
- Deep experience developing AI-native engineering workflows across design, implementation, debugging, testing, and automation, and raising the bar for how a team uses AI effectively
- Experience operating or building real-world review systems, whether human review, AI review, or adjacent workflows used for data annotation or customer-facing quality control
- Experience partnering closely with AI or ML teams, and familiarity with classifier-based systems or model-driven product workflows
- Deep experience in one or more backend-oriented languages commonly used for production systems, such as Go, Java, or similar
- Experience designing orchestrated pipelines or workflow-based systems, including technologies such as Temporal or similar frameworks
- Experience experimenting, iterating, and learning quickly against data to turn hypotheses into meaningful customer impact
- A data-driven mindset, including digging into problems deeply, validating outcomes against reality, and using evidence to guide next steps
- A track record of raising the bar for a team by improving systems, contributing to team culture, mentoring others, and helping teammates deliver better outcomes
- Curiosity and ambition to challenge existing product and engineering approaches to solving real-world problems
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