Autonomous Driving Planning & Prediction DL Engineer

Adapt Talent; California (MO); On-site; USD 210,000 - 350,000; Full time

Job summary

Adapt Talent in Santa Clara, CA is hiring a Planning & Prediction Deep Learning Engineer to design and optimize DL models for autonomous driving. You will work on planning and prediction, integrate models into the driving stack, and push the boundaries of vehicle intelligence.

The role emphasizes collaboration with cross-functional teams, research of state-of-the-art methods, and applying sensors data to improve decision-making and safety. On-site position with competitive compensation.

Qualifications

• A bachelor’s, master’s, or Ph.D. in Computer Science, Electrical Engineering, or a related field.
• Strong proficiency in TensorFlow, PyTorch, or similar frameworks.
• Proven experience deploying deep learning models for planning and prediction tasks.
• Familiarity with autonomous driving systems and sensor technologies.

Responsibilities

• Design, develop, and optimize deep learning models for planning and prediction in autonomous driving.
• Implement state-of-the-art algorithms for object detection, motion prediction, and behavior planning.
• Collaborate with cross-functional teams to integrate models into the autonomous driving stack.
• Research new DL advances and apply them to improve autonomous capabilities.
• Analyze and process sensor data to improve decision-making processes.
• Continuously evaluate model performance to meet safety and efficiency standards.
• Participate in data collection and annotation to support training.
• Contribute to simulation environments for testing and validation.

Skills

Deep learning

TensorFlow

PyTorch

Python

C++

Autonomous driving

Sensor data

CARLA simulation

Education

Bachelor's/Master/PhD in CS/EE or related field

Tools

CARLA

Job description

Adapt Talent in Santa Clara, CA is hiring a Planning & Prediction Deep Learning Engineer to design and optimize DL models for autonomous driving. You will work on planning and prediction, integrate models into the driving stack, and push the boundaries of vehicle intelligence.

The role emphasizes collaboration with cross-functional teams, research of state-of-the-art methods, and applying sensors data to improve decision-making and safety. On-site position with competitive compensation.