​Head of Engineering (AI,latest NoCode Platform)

Location San Francisco
Discipline: Connect AI, Computer Vision
Job type: Permanent
Salary: Up to $350k per annum
Contact name: Fadi Jawish

Contact email: Fadi.jawish@connectit-rec.com
Published: 3 months ago

Head of Engineering (AI,latest NoCode Platform)

Salary: Up to $350k plus equity and share options

Location: San Francisco / Hybrid

About the Company:

The company envisions a world where humanity can break free from the burdens of work, achieved through the development of an AI that can seamlessly access diverse tools and data. Their debut product, an AI assistant for professionals, is designed to streamline email, calendar, and meeting management.

A team of around 20 individuals, most of whom have collaborated closely for nearly two years, they have successfully secured substantial funding and have generated a waiting list of over 24,000 individuals.

Key Responsibilities:

·Remain at the forefront of AI developments, continuously seeking and incorporating the latest advancements (within the last three months) into a robust, scalable AI architecture that prioritizes speed and precision.

·Develop a strategic vision for the AI's evolution, ensuring it is at the forefront of industry trends. Your strategic approach will encompass current demands and future AI product needs while managing technical challenges within a startup context.

·Foster the growth and inspiration of a high-performing team of AI engineers through mentoring and guidance, cultivating a collaborative environment.

·Implement a range of data collection strategies.

·Collaborate with the team to make informed technical decisions regarding the utilization of specific libraries and tools, including DeepSpeed, Accelerate, Ray, and more.


·Profound understanding of the theory underpinning transformer models and a track record of experience in developing and deploying them.

·Proficiency with libraries that enhance the efficiency of training large models through various parallelism techniques and offloading strategies.

·Experience in guiding and mentoring AI researchers and engineers.


·A history of influential publications.

·Familiarity with cutting-edge parameter-efficient model tuning.

·Project experience in fields like computer vision or reinforcement learning.

·Proficiency in low-level CUDA/C++.