2 days ago
Base Salary
$180k - $260k/yr
Responsibilities
- Own the end-to-end ML lifecycle, including data strategy, preprocessing, training, evaluation, optimization, deployment, and monitoring.
- Develop and improve autonomous-driving models for perception, prediction, planning, and scene understanding.
- Design and optimize efficient neural networks using quantization, pruning, sparsification, compression, and efficient architectures.
- Integrate trained models into C++ autonomy systems and optimize real-time inference for production vehicle hardware.
- Profile and optimize neural networks using CUDA, TensorRT, and related technologies.
- Analyze model performance using simulation and real-world driving data, identify failure modes, and drive improvements.
- Build high-throughput pipelines for ML training, evaluation, data processing, and large-scale offline inference.
- Develop tooling for dataset curation, annotation, preprocessing, visualization, diagnostics, benchmarking, and continuous field-data feedback.
- Collaborate with perception, prediction, planning, infrastructure, systems, hardware, and autonomy teams to integrate reliable ML components into the vehicle platform.
Requirements
- Master’s or PhD in Computer Science, Machine Learning, Robotics, Electrical Engineering, Statistics, Optimization, or a related field.
- Strong Python skills and experience with PyTorch or TensorFlow.
- Strong C++ skills and experience integrating ML models into high-performance production systems.
- Deep understanding of data curation, training, evaluation, ablation studies, deployment, and inference optimization.
- Experience deploying and optimizing neural networks for real-time, embedded, robotics, autonomous-driving, or other performance-constrained systems.
- Experience with quantization, pruning, compression, and efficient neural network architectures.
- Experience with software architecture, profiling, latency optimization, system-level debugging, and data-flow analysis.
- Experience with CUDA and TensorRT is highly desirable.
- Experience with cloud-based ML training and evaluation pipelines, preferably Azure.
- Experience with transformers, multimodal models, diffusion models, world models, end-to-end driving models, autonomous driving, robotics, safety-critical real-time ML systems, publications, or large-scale production ML systems is preferred or a plus.
Benefits
- Onsite five days per week at the Santa Clara, California office.
- Inclusive and collaborative work environment with opportunities to contribute to autonomous freight, resilient supply chains, and sustainability.
About Gatik AI
Gatik AI builds and operates autonomous middle‑mile trucking networks for retailers and consumer brands, delivered as a transportation‑as‑a‑service offering. Its Level 4, Class 3–7 trucks move B2B freight on short‑haul, repeatable routes, with commercial deployments in Texas, Arkansas, and Ontario, including a fully driverless service launched with Walmart in 2021. Founded in 2017 and headquartered in Santa Clara, it integrates software and hardware to run driverless deliveries between warehouses and stores.