Senior Software Engineer - Safety Detection Precision

Samsara Samsara · Enterprise · London, United Kingdom · Safety

Senior Software Engineer to build and evolve core systems that review AI safety detections, improve precision, and automate triage. The role focuses on the intersection of backend systems, data, and AI-driven decisioning to enhance customer-facing product quality and internal review efficiency. This involves owning complex projects end-to-end, partnering with AI/ML teams, and utilizing AI-assisted engineering workflows.

What you'd actually do

  1. Build and evolve the core systems that review safety detections and determine which events are surfaced to customers
  2. Improve detection precision by developing intelligent approaches to identifying ambiguous cases, deflecting low-value reviews, and automating triage where confidence is high
  3. Work at the intersection of backend systems, data, and AI-driven decisioning to improve both customer-facing product quality and internal review efficiency
  4. Partner closely with product, design, AI and ML infra to turn real-world review outcomes into better model feedback loops and higher-quality safety detections over time
  5. Own complex projects end-to-end, from shaping the approach and technical design through rollout, measurement, and iteration in production

Skills

Required

  • 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

Nice to have

  • 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

What the JD emphasized

  • AI detection of safety risk
  • customer trust
  • AI-first engineer
  • AI-native engineering workflows

Other signals

  • AI detection of safety risk
  • improve detection precision
  • automate triage
  • AI-driven decisioning
  • model feedback loops
  • higher-quality safety detections