Jobs at Gatik

• Provide day-to-day IT support for laptops, desktops, peripherals, mobile devices, and office technology
• Set up and configure new hire equipment, user accounts, access permissions, and software

• Develop and execute test plans for autonomy software, vehicle systems, and new feature releases.
• Perform functional, integration, regression, and release validation testing.

• Support autonomous truck deployments, fleet launches, and operational expansions.
• Execute deployment readiness assessments and validation activities prior to vehicles entering service.

• Distributed Training & ML Systems Support

Scale Research Workloads: Enable researchers to scale complex models (VLA, World Models) across multi-node setups using PyTorch Distributed, and Ray Train.
Performance Optimization: Architect and optimize multi-GPU setups, ensuring efficient model parallelism and data parallelism techniques across H100/A100 clusters.
Networking & Hardware Tuning: Optimize low-level communication (e.g., NCCL tuning, InfiniBand, or RoCE v2) to minimize latency for 3D Gaussian Splatting (3DGS) and large-scale training.
Intelligent Resource Scheduling: Optimize hardware utilization and cost-efficiency through Kubernetes-native GPU scheduling (NVIDIA GPU Operator, KubeFlow).
Inference Performance Engineering: Deploy and scale optimized model artifacts using TensorRT, ONNX Runtime, and Triton Inference Server, fine-tuning pipelines for both real-time and batch processing

• Cloud-Native Orchestration & Kubernetes

Advanced K8s Management: Architect and maintain mission-critical Kubernetes clusters optimized for heavy GPU/TPU workloads.
GPU Scheduling: Implement and optimize Kubernetes-native GPU scheduling (NVIDIA GPU Operator) to ensure maximum hardware utilization.
Infrastructure as Code: Drive the "Everything as Code" philosophy using Terraform, Helm, and cloud-native tools.
Self-Healing Infrastructure: Deploy Autonomous AI Agents (LangGraph, CrewAI) to monitor cluster health and enable automated triage of hardware failures and NCCL timeouts.

• Lead integration efforts of software and hardware components within the autonomous driving system, ensuring seamless operation and robust performance.
• Develop, execute, and maintain test plans, cases, and procedures for validating system-level functionality, focusing on critical areas such as perception, navigation, and control.

• Mapping Pipeline Development: Contribute to the design, development, and expansion of the HD Mapping production pipeline.
• Data Processing and Validation: ○ Process, clean, and validate large-scale LiDAR point cloud datasets. ○ Extract and refine road-based linear and polygonal features. ○ Annotate and validate 3D objects and roadway furniture. ○ Perform topology validation of road networks (lane connectivity, intersection logic, turn constraints).

• Frontend Development: Build a responsive, high-performance UI using React/TypeScript. Implement 3D visualization components using Three.js or WebGL to render simulation environments and sensor data.
• Backend & API Design: Architect scalable REST and WebSocket APIs to handle real-time telemetry and simulation control commands.

• ROS2 Stack Integration: Develop and maintain the ROS2 middleware layers (C++/Python) that allow AI models to receive sensor data and send control commands within the simulation.
• Scenario Engineering: Script and implement dynamic testing scenarios (e.g., traffic interactions, pedestrian behavior, triggered events) using Python or simulator-specific APIs.

• Identity Governance & RBAC: Design and manage comprehensive RBAC frameworks. Conduct regular access reviews and audits for SOC2/ISO 27001 compliance.
• Automated Lifecycle Management: Build and maintain automated onboarding/offboarding workflows using Google workspace, Okta Workflows, MSFT Entra, or Python.

• Design, develop, and optimize sensor-based localization and odometry algorithms to improve the positioning accuracy of autonomous vehicles.
• Implement algorithms for sensor fusion, utilizing data from IMU, GPS, Lidar, and other sensors to create a robust, reliable localization pipeline.

• Design, implement, integrate, and support real-time mission-critical software for Gatik’s autonomy stack.
• Work with the research engineers to develop maintainable, testable, and robust software designs.

• Build and maintain ETL pipelines for ingestion, aggregation, and presentation of data from our fleet of live autonomous trucks, ensuring scalability, reliability, and performance.
• Design and implement solutions for upgrading and deploying on-board vehicle infrastructure and AV stack software to production vehicles with minimal downtime.

• Upgrade and maintain both physical and cloud infrastructure used for offloading data from our autonomous vehicle fleet.
• Partner with the infrastructure and platform engineering teams to monitor, maintain, and troubleshoot our on-premises data offload and CI systems.

• Design and develop real-time Visual Odometry pipelines using monocular, stereo, or RGB-D camera inputs.
• Implement robust camera-based localization algorithms, including visual-inertial odometry (VIO), feature tracking, motion estimation, and scale recovery.