| Company |
iMETALX |
| Job title |
AI/ML Engineer |
| Job location |
Sausalito, California, US |
| Type |
Full Time |
Responsibilities:
- Design, develop, and implement reinforcement learning algorithms for autonomous control and maneuvering of vehicles.
- Develop and deploy deep neural networks for perception, decision-making, and control tasks.
- Integrate RL models with vehicle control systems to optimize performance in complex environments.
- Conduct simulations and real-world testing to validate control algorithms and RL models.
- Collaborate with cross-functional teams to define requirements and specifications for autonomy and control systems.
- Develop and maintain software in C++ and Python, utilizing relevant libraries and frameworks for RL and deep learning.
- Optimize code for performance and scalability on various platforms, including embedded systems.
- Stay updated with the latest research and advancements in reinforcement learning, deep learning, and control systems.
- Document software designs, algorithms, and development processes.
- Write product or system development code.
- Participate in, or lead, design reviews with peers and stakeholders to decide amongst available technologies.
- Explore the application of Machine Learning (ML) and Physics-based AI to enhance autonomy.
- Conduct research and devise novel algorithms to guide product strategy.
- Develop infrastructure that enables product scalability.
Requirements & Skills:
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field. PhD is a plus.
- 5-10 years of professional experience in software engineering, with a focus on reinforcement learning and control systems.
- Extensive experience with deep neural networks and reinforcement learning frameworks (e.g., TensorFlow, PyTorch, Keras).
- Strong proficiency in C++ and Python, along with relevant libraries and tools for RL development.
- Demonstrated experience in the design and implementation of control systems for autonomous vehicles in air, ground, sea, or space environments.
- Solid understanding of vehicle dynamics, motion planning, and control theory.
- Proven ability to develop and optimize algorithms for real-time applications.
- Experience with simulation tools and environments (e.g., Gazebo, ROS, MATLAB/Simulink).
- Strong analytical and problem-solving skills, with a keen attention to detail.
- Excellent communication and collaboration skills.
- Experience with embedded systems and real-time operating systems (RTOS).
- Familiarity with hardware integration and sensor fusion techniques.
- Knowledge of safety and reliability considerations for autonomous systems.
- Experience with version control systems (e.g., Git) and software development methodologies (e.g., Agile, CI/CD, DevSecOps).
