Jobs at Gatik

• Collaborate with a team of business, technical, product and operations individuals to design and optimize Gatik’s Autonomous Networks.
• Drive the implementation and scaling of tools, capabilities, and processes necessary to achieve goals of the NDO team.

• End-to-End Model Development: Own the full ML lifecycle, including data strategy, preprocessing, training, evaluation, optimization, deployment, and monitoring.
• Autonomous Driving Models: Develop and improve models supporting perception, prediction, planning, and scene understanding.

• DbW Safety Architecture: Define the functional safety architecture for redundant steering, braking, and propulsion control systems integrated into Gatik’s vehicle platforms.
• OEM & Actuation Integration: Collaborate with commercial vehicle OEMs and Tier-1 DbW providers to evaluate DbW interfaces, safety manuals, and functional safety compliance (ISO 26262).

• SIL Test Strategy & Automation: Design and scale automated SIL testing pipelines integrated into cloud-based CI/CD workflows for daily regression and release gate evaluation.
• Scenario Creation & Parameter Variation: Generate complex, high-fidelity synthetic scenarios (urban/suburban middle-mile routes, edge cases, adverse weather, severe traffic interactions) using scenario definition standards (OpenSCENARIO, ASAM).

• Functional Safety: Conduct hardware functional safety activities including FMEDA (Failure Modes, Effects, and Diagnostic Analysis), PMHF (Probabilistic Metric for random Hardware Failures), and Single Point Fault Metrics (SPFM).
• Component Safety & Vendor Management: Evaluate, select, and qualify automotive-grade (AEC-...

• HIL Architecture & Maintenance: Design, construct, and maintain multi-ECU HIL test benches representing complete AV vehicle electronics.
• Sensor Injection & Signal Simulation: Integrate sensor simulation technology into real-time test setups.

• System Safety Concept Development: Define and maintain the Functional Safety Concept (FSC) and Technical Safety Concept (TSC) for Gatik’s Level 4 autonomous system in accordance with ISO 26262 (up to ASIL D).
• Hazard Analysis & Risk Assessment (HARA): Lead system-level HARAs, STPA (System-Theoretic ...

• Public Road Validation Strategy: Define and execute on-road structured testing and shadow fleet evaluation programs for new software builds across commercial customer corridors.
• Route & Map Validation: Validate map updates, route configurations across customer ODDs prior to driverless sign-off.

• SOTIF & ML Safety Architecture: Lead the implementation of ISO 21448 (SOTIF) and UL 4600 frameworks across Gatik's AI/ML pipelines.
• Safety Requirements for Learned Systems: Derive safety requirements and performance boundaries (e.g., false positive/negative limits, edge-case coverage metrics) for neural networks and deep learning models.

• Build and improve vehicle chassis controls software for integration on common ECU hardware for vehicle controls.
• Create functionally safe software by following common automotive standards for functional safety.

• 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

• 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.