Top Tech Jobs & Startup Jobs

Design and implement real-time perception and sensor-fusion algorithms (LiDAR, camera, radar) for autonomous trucks. Build and optimize deep learning models, manage large-scale datasets, run field tests and simulations, and develop validation frameworks to ensure robust, safe perception in diverse driving conditions.

Provide onsite day-to-day IT support for laptops, desktops, mobile devices, printers, and AV. Configure new-hire equipment and accounts, troubleshoot hardware/software/network issues, maintain inventory and perform routine security/connectivity checks, document processes, and coordinate with vendors for office infrastructure and networking support.

Design, build, and scale the AI platform for distributed multi-GPU training, experiment tracking, and model deployment. Optimize GPU clusters, networking (NCCL/InfiniBand), Kubernetes-native scheduling, and inference serving (TensorRT, Triton). Develop agentic automation for cluster health, CI/CD, and data curation while integrating ML lifecycle tooling and observability.

Design, build, and operate large-scale GPU/TPU cloud infrastructure and data pipelines to support distributed training, MLOps, model serving, and observability. Manage Kubernetes clusters, GitOps CI/CD, experiment tracking, and optimize networking and multi-node training performance for research and production workloads.

Integrate and maintain a ROS2-based autonomy stack inside high-fidelity simulators, author dynamic adversarial scenarios, configure simulated sensors, enable headless Docker orchestration for large-scale cloud testing, stream simulation states to a web dashboard, and manage serialized ROS2 message logging for analysis and playback.

Design, implement, and optimize real-time motion planning and decision-making systems for autonomous vehicles. Develop lattice-, sampling-, and optimization-based planners, integrate perception/prediction/control constraints, debug in simulation and on-road, and optimize C++ infrastructure for safe, deployable trajectory generation and evaluation.

Lead design and implementation of multi-modal perception: object detection, tracking, and sensor fusion. Build data pipelines, train and optimize perception models, develop scalable training/evaluation tools, and integrate systems for real-world autonomous vehicle deployment.

Design and implement real-time sensor fusion, GPS-IMU fusion, and SLAM-based localization and odometry algorithms for autonomous vehicles. Integrate localization with perception, mapping, and control, validate in simulation and real-world tests, optimize for real-time constraints, and debug using large-scale field data to improve robustness and accuracy.

Design, build, and operate scalable data ingestion, CI/CD, and deployment infrastructure for a growing autonomous vehicle fleet. Implement IaC, containerized deployments, ETL pipelines, simulation integration into CI, and coordinate on-board software upgrades and site rollouts to enable reliable AV software development and production deployments.

Design and implement identity and SaaS integration solutions: build Zero-Touch automated onboarding/offboarding, enforce RBAC and least-privilege, run access reviews for SOC2/ISO 27001, integrate SaaS via SAML/OIDC/SCIM, deploy IGA tooling (Lumos/IdenHQ), and automate workflows with Zapier, Python or PowerShell across a 50+ tool SaaS stack.