ML Systems Engineer

Posted 17 January 2024
Salary 200000 - 300000
LocationMountain View
Job type Permanent
Discipline Data & AI
Contact NameAlexis Navarro

Job description


Our client is an autonomous driving Saas company, developing software that can be embedded into any modern vehicle - making autonomous driving affordable and accessible to all!

As a Machine Learning Systems Engineer, you will play a pivotal role in advancing the cutting-edge technology that powers our their autonomous driving solutions. 

Key Responsibilities:

  1. System Architecture: Collaborate with cross-functional teams to design and architect scalable and efficient machine learning systems for autonomous driving applications.

  2. Algorithm Development: Develop and implement machine learning algorithms to enhance perception, decision-making, and control systems in autonomous vehicles.

  3. Integration: Integrate machine learning models into the overall software stack, ensuring seamless interaction with other components of the autonomous driving system.

  4. Optimization: Optimize algorithms and models for performance, taking into consideration real-time constraints and resource limitations inherent in the autonomous driving environment.

  5. Testing and Validation: Conduct thorough testing and validation of machine learning systems to ensure reliability, safety, and compliance with industry standards.

  6. Collaboration: Work closely with software engineers, data scientists, and hardware engineers to create a cohesive and integrated autonomous driving solution.

  7. Continuous Learning: Stay abreast of the latest developments in machine learning, artificial intelligence, and autonomous driving technologies, and apply this knowledge to enhance system capabilities.


  • Bachelor's, Master's, or Ph.D. in Computer Science, Electrical Engineering, or a related field.
  • Proven experience in designing and implementing machine learning systems for real-world applications, preferably in autonomous driving or a related field.
  • Proficiency in programming languages such as Python, C++, or Java.
  • Strong understanding of machine learning frameworks and libraries.
  • Experience with system integration and optimization for embedded systems.
  • Excellent problem-solving and communication skills.