<h3><span style="font-family: 'times new roman', times, serif;">Who we are</span></h3> <p><span style="font-family: 'times new roman', times, serif;">Gatik, the leader in autonomous middle-mile logistics, is revolutionizing the B2B supply chain with its autonomous transportation-as-a-service (ATaaS) solution and prioritizing safe, consistent deliveries while streamlining freight movement by reducing congestion. The company focuses on short-haul, B2B logistics for Fortune 500 retailers and in 2021 launched the world’s first fully driverless commercial transportation service with Walmart. Gatik's Class 3-7 autonomous trucks are commercially deployed across major markets, including Texas, Arkansas, and Ontario, Canada, driving innovation in freight transportation. </span></p> <p><span style="font-family: 'times new roman', times, serif;">The company's proprietary Level 4 autonomous technology, Gatik Carrier™, is custom-built to transport freight safely and efficiently between pick-up and drop-off locations on the middle mile. With robust capabilities in both highway and urban environments, Gatik Carrier™ serves as an all-encompassing solution that integrates advanced software and hardware powering the fleet, facilitating effortless integration into customers' logistics operations. </span></p> <h3><span style="font-family: 'times new roman', times, serif;"><strong>About the role</strong> </span></h3> <p><span style="font-family: 'times new roman', times, serif;">We are seeking a high impact, technically deep Machine Learning Engineer to develop, optimize, and deploy production ML models across our autonomous vehicle (AV) stack. This role is ideal for engineers who enjoy building models end-to-end - from data and training through optimization and real-time deployment on autonomous vehicles.</span></p> <p><span style="font-family: 'times new roman', times, serif;">You will work closely with perception, prediction, planning, infrastructure, systems, and hardware teams to ensure models are efficient, scalable, reliable, and production-ready for both on-vehicle and cloud workflows.</span></p> <p><span style="font-family: 'times new roman', times, serif;">This role is onsite 5 days a week at our Santa Clara, CA office!</span></p> <h3><span style="font-family: 'times new roman', times, serif;"><strong>What you'll do</strong></span></h3> <ul> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>End-to-End Model Development:</strong> Own the full ML lifecycle, including data strategy, preprocessing, training, evaluation, optimization, deployment, and monitoring.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Autonomous Driving Models:</strong> Develop and improve models supporting perception, prediction, planning, and scene understanding.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Efficient Neural Network Design:</strong> Optimize models using techniques such as quantization, pruning, sparsification, compression, and efficient architecture design to meet strict latency, compute, memory, and power constraints.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Real-Time Deployment:</strong> Integrate trained models into C++-based autonomy systems and optimize inference for production vehicle hardware.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Model Optimization:</strong> Profile and optimize neural networks using CUDA, TensorRT, and related technologies.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Simulation and Evaluation:</strong> Analyze model performance using simulation and real-world driving data, identify failure modes, and drive improvements.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Scalable ML Infrastructure:</strong> Build high-throughput pipelines for training, evaluation, data processing, and large-scale offline inference.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Data Workflows and Tooling:</strong> Develop reliable pipelines for dataset curation, annotation, preprocessing, visualization, diagnostics, benchmarking, and continuous feedback from field data.</span></li> <li><s