Job Posting for (Senior) Machine Learning Engineer at CONXAI
We are developing an AI Platform for the Architecture, Engineering, and Construction (AEC) industry. Our platform leverages advanced AI to enable construction domain experts to create complex use cases efficiently.
Tasks
We are looking for a Machine Learning Engineer, experienced in Deep Learning, Computer Vision and Natural Language Processing, to drive the development and production of deep learning models. The role requires you to operate as both an individual contributor, collaborate with a team of highly skilled Machine Learning Engineers, and manage talented Machine Learning interns.
Prototype ML models on real-world data, and bring it to production
Deliver production-grade ML models for AEC industry use cases
Design and adapt system architecture that satisfies product requirements
Manage the ML Interns to drive model customization
Requirements
We are looking for candidates with demonstrable experience in Deep Learning. In addition to theoretical knowledge, the candidate should have extensive industry experience in taking deep learning models to production and scaling on large-scale customer data.
MS/PhD in Deep Learning
3 years of Industrial experience in deep learning.
At least 2 years of leading Machine Learning (Deep Learning) projects.
Experience in Computer Vision and Natural Language Processing. Specifically, experience working with autoregressive temporal models like Transformers, or RNNs
Working knowledge of VLMs and LLMs
Exceptional implementation experience in developing new deep learning models in PyTorch
Thorough understanding of software design
Fluent and articulate in English
Benefits
Dynamic and collaborative team working on cutting-edge technology
Opportunities for professional growth and development
If your compensation planning software is too rigid to deploy winning incentive strategies, it’s time to find an adaptable solution.
Compensation Planning
View Core, Job Family, and Industry Job Skills and Competency Data for more than 15,000 Job Titles
Skills Library