ML Engineer - Autonomous Driving, Real-Time Inference

Gatik; Santa Clara, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Gatik seeks a high-impact Machine Learning Engineer to develop, optimize, and deploy production ML models across the autonomous vehicle stack. You will collaborate with perception, prediction, planning, infrastructure, systems and hardware teams to ensure models are efficient and production-ready for both on-vehicle and cloud workflows.

The role is onsite 5 days a week at the Santa Clara, CA office, with responsibilities spanning model development, optimization, simulation, and scalable ML

Qualifications

• MS or PhD in CS/ML/Robotics/EE/Statistics/Optimization or related field.
• Open to all experience levels; leveling determined by depth of technical skills.
• Strong Python skills with PyTorch or TensorFlow.
• Experience deploying neural networks in real-time, embedded, autonomous driving or similar systems.
• Experience with model optimization techniques: quantization, pruning, compression, efficient architectures.
• Experience with software architecture, profiling, latency optimization, and data-flow analysis.
• Experience with CUDA and TensorRT is highly desirable.
• Experience with cloud-based ML training/evaluation pipelines, preferably Azure.

Responsibilities

• Develop and improve models for perception, prediction, planning, and scene understanding.
• Optimize models for latency, compute, memory, and power constraints.
• Profile and optimize neural networks using CUDA and TensorRT.
• Build high-throughput pipelines for training, evaluation, and large-scale offline inference.
• Collaborate with autonomy, systems, hardware, and infrastructure teams to integrate ML components.

Skills

Python

PyTorch

TensorFlow

Embedded systems

Model optimization

Education

MS/PhD in CS/ML/Robotics/EE

Tools

CUDA

TensorRT

Job description

Gatik seeks a high-impact Machine Learning Engineer to develop, optimize, and deploy production ML models across the autonomous vehicle stack. You will collaborate with perception, prediction, planning, infrastructure, systems and hardware teams to ensure models are efficient and production-ready for both on-vehicle and cloud workflows.

The role is onsite 5 days a week at the Santa Clara, CA office, with responsibilities spanning model development, optimization, simulation, and scalable ML