Machine Learning Architect (Software/Hardware Co-Design)

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 and innovative Machine Learning Research Scientist / Architect with expertise in software/hardware co-design to drive advancements in autonomous driving technologies. This role offers a unique opportunity to bridge the gap between machine learning algorithms and hardware design, contributing to high-performance, efficient, and scalable solutions for AI-driven systems.

Responsibilities:

• Conduct in-depth research and analysis of cutting-edge machine learning algorithms, with a primary focus on applications in autonomous driving.
• Monitor and forecast industry trends in AI technologies to identify opportunities for innovation and improvement.
• Evaluate the computational and memory requirements of various AI models and operators, identifying optimization opportunities.
• Collaborate closely with chip architects and engineers to design and implement software/hardware co-designed solutions that enhance chip performance, efficiency, and scalability.
• Develop comprehensive technical documentation and presentations to effectively communicate complex concepts to both technical and non-technical audiences.
• Stay connected with academic and industry research communities to remain at the forefront of AI and machine learning advancements.

Qualification/ Requirements:

• Education: Master’s or PhD in Computer Science, Electrical Engineering, or a related technical field with a strong focus on machine learning.
• Experience: Proven experience in developing and analyzing machine learning algorithms.
• Programming Skills: Proficiency in programming languages such as Python and C++.
• ML Frameworks: Hands-on experience with machine learning frameworks like TensorFlow and PyTorch, and deploying them on hardware accelerators.
• Collaboration: Demonstrated ability to work effectively in a team-oriented, cross-disciplinary environment.
• Co-Design Expertise: Strong understanding of software/hardware co-design principles and their impact on system performance is highly preferred.