ADAS Engineer

Astemo Ltd

$100K — $130K *
Manufacturing & Automotive
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in AI/ML deployment in an automotive setting.
  • Master's or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
  • Proficiency in C/C++ (preferably modern C++) and Python programming languages.
  • Familiarity with major ML frameworks and inference runtimes.
  • Hands-on experience with model compression techniques and trade-offs between accuracy and performance.
  • Knowledge of AD/ADAS systems and embedded SoC architectures.
  • Excellent communication and presentation skills for stakeholder engagement.

Responsibilities

  • Deploy and optimize AI/ML models on embedded automotive SoCs.
  • Apply advanced optimization techniques to maintain model accuracy.
  • Profile and fine-tune workloads across various compute resources.
  • Develop AI workload orchestration and scheduling methods under constraints.
  • Diagnose deployment issues and establish validation approaches.
  • Manage trade-offs across several performance metrics, providing recommendations.
  • Collaborate with cross-functional teams to integrate advanced developments into production.

Benefits

  • Opportunity to work at the forefront of AI/ML in the automotive industry.
  • Exposure to a variety of projects as priorities change.
  • Collaboration with high-profile engineering and development teams.
  • Possibility for domestic and international travel to support projects.
  • Flexibility in addressing evolving project demands.
Full Job Description
Job Family:

Engineering

Job Description:

Position Overview and Objective

Astemo's Advanced Development Division is hiring a Senior Engineer to own the deployment and optimization of AI/ML workloads, including ADAS perception models, LLMs, and Vision-Language-Action (VLA) models, on embedded automotive SoCs. The engineer will work across multiple areas as priorities evolve and is expected to contribute to both current development needs and emerging software initiatives.

Job Responsibilities:
  • Deploy and optimize AI/ML models on embedded automotive SoCs to meet performance, memory, and efficiency targets.
  • Apply advanced model optimization techniques while preserving accuracy and intended behavior.
  • Profile inference pipelines and tune workloads (kernels and model graphs) across heterogeneous compute resources for real-time use.
  • Develop orchestration and scheduling approaches for AI workloads across heterogeneous compute resources under real-time and power/thermal constraints.
  • Diagnose deployment-related issues and define validation approaches to evaluate new techniques.
  • Manage and evaluate trade-offs across accuracy, latency, throughput, memory footprint, and energy consumption; produce data-driven recommendations.
  • Collaborate with cross-functional teams to transition advanced work into the production stack.


Qualifications:
  • Knowledge of AD/ADAS systems and automotive hardware platforms.
  • Solid understanding of deep learning fundamentals and the numerical behavior of neural networks.
  • Hands-on experience with major ML frameworks and inference runtimes.
  • Practical experience with model compression techniques and the associated accuracy/performance trade-offs.
  • Working knowledge of embedded SoC architectures and their implications for ML workload performance.
  • Strong programming proficiency in C/C++ (modern C++ preferred) and Python.
  • Familiarity with profiling tools and a structured approach to performance analysis.
  • Exposure to low-level optimization techniques for AI workloads on embedded accelerators.
  • Flexibility and willingness to work across multiple software layers as project needs evolve.
  • Excellent communication and presentation skills, with the ability to influence and persuade stakeholders at all levels of the organization.


Additionally, the ability to work independently with minimal direction is required as are strong verbal and written communication skills. Experience with PCs and application software, such as MS Office tools, is also required.

Education: Master's or Ph.D. degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.

Experience: Minimum of 5+ years with Masters and 1+ years with Ph.D. or relevant industrial experience is required.

Job level is determined by various factors such as organization size, responsibility, career stage, and capabilities.

Supervisory Responsibilities: n/a

Working conditions:

Physical Demands: Required to sit or stand for long periods of time. The employee may occasionally lift and/or move up to 25 pounds.

Travel: Domestic and international may be required as needed. The candidate will occasionally need to travel to multiple global locations to support project development

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