Conxai Technologies GmbH

Software Development

11-50

Germany

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
*   Modern and inclusive work environment
*   Stock options
*   Flexible work hours

Employee

Professional / Experienced

<p>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.</p>
<h2 id="tasks">Tasks</h2>
<p>We are looking for a <strong>Machine Learning Engineer</strong>, 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.</p>
<ul>
<li>Prototype ML models on real-world data, and bring it to production</li>
<li>Deliver production-grade ML models for AEC industry use cases</li>
<li>Design and adapt system architecture that satisfies product requirements</li>
<li>Manage the ML Interns to drive model customization</li>
</ul>
<h2 id="requirements">Requirements</h2>
<p>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.</p>
<ul>
<li>MS/PhD in Deep Learning</li>
<li>3+ years of Industrial experience in deep learning.</li>
<li>At least 2+ years of leading Machine Learning (Deep Learning) projects.</li>
<li>Experience in Computer Vision and Natural Language Processing. Specifically, experience working with autoregressive temporal models like Transformers, or RNNs</li>
<li>Working knowledge of VLMs and LLMs</li>
<li>Exceptional implementation experience in developing new deep learning models in PyTorch</li>
<li>Thorough understanding of software design</li>
<li>Fluent and articulate in English</li>
</ul>
<h2 id="benefits">Benefits</h2>
<ul>
<li>Dynamic and collaborative team working on cutting-edge technology</li>
<li>Opportunities for professional growth and development</li>
<li>Modern and inclusive work environment</li>
<li>Stock options</li>
<li>Flexible work hours</li>
</ul>


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