ML Architect: Software/Hardware Co-Design for Autonomous Driving

Black Sesame Technologies (Singapore) Pte Ltd; Singapore; On-site; SGD 120,000 - 170,000; Full time

Job summary

Black Sesame Technologies is seeking a talented Machine Learning Research Scientist/Architect with expertise in software/hardware co-design to advance autonomous driving AI. This role bridges ML algorithms and hardware design to deliver high-performance, scalable solutions.

You will conduct research on cutting-edge ML methods for autonomous driving, collaborate with chip architects, and document findings for technical and non-technical audiences.

Qualifications

• Master’s or PhD in Computer Science, Electrical Engineering, or related field with ML focus.
• Proven experience in developing and analyzing ML algorithms.
• Proficiency in Python and C++.
• Hands-on experience with TensorFlow and PyTorch, deploying on hardware accelerators.
• Strong collaboration in cross-disciplinary environments.
• Co-design expertise preferred.

Responsibilities

• Conduct in-depth research and analysis of ML algorithms for autonomous driving.
• Forecast industry AI trends to identify opportunities for innovation.
• Evaluate computational and memory requirements of AI models and identify optimization opportunities.
• Collaborate with chip architects and engineers to design software/hardware co-designed solutions.
• Develop technical documentation and presentations for both technical and non-technical audiences.
• Engage with academic and industry research communities to stay at the forefront of AI and ML advancements.

Skills

Python

C++

Cross-functional teamwork

Collaboration

Education

Master’s or PhD in Computer Science or Electrical Engineering

Tools

TensorFlow

PyTorch

CUDA

Job description

Black Sesame Technologies is seeking a talented Machine Learning Research Scientist/Architect with expertise in software/hardware co-design to advance autonomous driving AI. This role bridges ML algorithms and hardware design to deliver high-performance, scalable solutions.

You will conduct research on cutting-edge ML methods for autonomous driving, collaborate with chip architects, and document findings for technical and non-technical audiences.