ADAS Engineer - J0050763

Astemo Ltd.; Farmington Hills (MI); On-site; USD 120,000 - 180,000; Full time

Job summary

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

Responsibilities include deploying and optimizing models, profiling inference pipelines, and developing orchestration

Qualifications

• Master’s or Ph.D. required in a related field.
• 5+ years of industrial ML deployment experience.
• Experience with embedded SoCs and automotive platforms.

Responsibilities

• Deploy and optimize AI/ML workloads on embedded automotive SoCs.
• Profile inference pipelines and tune workloads for real-time performance.
• Develop orchestration strategies across heterogeneous compute resources.
• Collaborate with cross-functional teams to productionize advanced methods.
• Assess trade-offs among accuracy, latency, memory and energy.

Skills

C/C++ programming

Python

Performance profiling

Model optimization

Education

Master’s or Ph.D. in Computer Science/Engineering

Tools

TensorFlow

PyTorch

ONNX

TensorRT

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.

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