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Build, optimize, and scale real-time software processing high-throughput 3D LiDAR data. Collaborate with perception algorithm teams to deliver production-ready systems, deploy and scale pipelines using Kubernetes and cloud services, optimize performance across edge and containerized environments, develop Python tooling and tests, integrate GenAI capabilities, and own technical work from architecture through production deployment.

Develop and optimize real-time algorithms for 3D LiDAR perception, including point-cloud clustering, classification, semantic segmentation, and ground detection. Responsibilities include researching solutions, designing algorithmic improvements, creating evaluation datasets, integrating modules into C++ software, conducting unit and system testing, characterizing performance, and documenting results. The role requires machine learning and deep learning expertise, independent ownership, collaboration, and fluent English.

Develop and optimize real-time algorithms for 3D LiDAR perception, including point-cloud clustering, classification, semantic segmentation, and ground detection. Responsibilities include researching solutions, designing algorithm modules, building evaluation datasets, integrating developments into C++ software, conducting unit, performance, and system testing, and documenting results. The role requires collaboration across teams while independently owning algorithmic projects.

Develop and optimize Unity-based LiDAR simulation features, collaborate with R&D, 3D artists and engineers, prioritize releases and bug fixes, redesign codebase, build dynamic simulation tools for model training and demos, and continue crowd simulation and 3D asset integration while profiling for performance.

Maintain stability of live customer deployments: validate operational handovers, triage and reproduce application defects, escalate with targeted logs, perform production updates and health audits, author runbooks, conduct RCA, and participate in scheduled night and weekend on-call rotations.

Outsight encourages individuals to submit spontaneous applications for positions that fit their skills and expertise. Candidates can upload resumes for review by the recruitment team.

Design and implement backend intelligence for autonomous spatial workflows: architect multi-step agentic execution paths, state tracking and memory systems, consume streaming MCP data, and integrate alerting/notification pipelines (Slack, webhooks) driven by autonomous decisions.

Design and build high-performance, responsive web applications that visualize 3D/LiDAR spatial data, streaming events, and multi-tenant telemetry. Implement modular real-time chatbot and rich-text messaging components exposing AI agent steps. Optimize rendering and state handling under heavy live-data traffic. Provide technical mentorship to incoming frontend interns and drive generative UI workflows and rapid prototyping.

Design, build, and maintain production ELT pipelines for high-volume streaming spatial and telemetry data. Architect Databricks/AWS schemas for ultra-low latency and zero-data-loss. Develop and optimize a central semantic layer using Cube.js for reliable data consumption. Ensure LLM-agent friendly semantic modeling, automation of pipeline unit tests, and package integration blueprints for Professional Services.