Lead Engineer – Large Concept Model (LCM) Development

About Us:

We are an innovative startup focused on creating a next-generation knowledge mining and curated internet platform. Leveraging cutting-edge AI technologies, we're pioneering the development of Large Concept Models (LCMs) to transform how specialized knowledge is accessed and utilized across various professional domains, including legal, medical, scientific research, and financial sectors.

Role Overview:

We are seeking an experienced AI Engineer with a deep understanding of transformer-based architectures, NLP, and conceptual AI methodologies to lead the development of our proprietary Large Concept Model (LCM). You'll collaborate closely with our existing team of ML engineers, data scientists, and software developers to design, build, and deploy LCMs capable of efficiently structuring, retrieving, and synthesizing complex, multi-domain knowledge.

Responsibilities:

• Architect, design, and implement our Large Concept Model (LCM) pipeline, including concept encoders, core transformer architectures, and decoders.
• Lead the selection, curation, and preprocessing of training datasets suitable for LCM training.
• Drive experimental research to optimize LCM performance on tasks such as summarization, semantic retrieval, and multilingual content integration.
• Collaborate with engineers to integrate LCM into our platform, ensuring scalability, efficiency, and robustness.
• Monitor model performance, diagnosing and addressing model drift, performance bottlenecks, and accuracy issues.
• Document methodology, results, and processes clearly and effectively for internal and external stakeholders.
• Stay current with cutting-edge AI research, proposing and implementing enhancements to maintain technical leadership in conceptual AI modeling.

Required Qualifications:

• Master's or Ph.D. or relevant experience in AI, NLP, Machine Learning, or related fields.
• 5+ years of experience in AI/NLP engineering with a proven track record of building and deploying transformer-based large-scale AI models.
• Deep understanding of transformer models (GPT, BERT, RoBERTa, T5, etc.), and experience with concept-level modeling or advanced semantic embedding techniques.
• Strong proficiency in Python and experience with machine learning frameworks such as PyTorch, Hugging Face Transformers, TensorFlow.
• Demonstrated capability in building efficient, scalable ML pipelines from experimental to production environments.
• Experience with cloud infrastructure (AWS preferred), GPU training/inference, Docker, Kubernetes, or related technologies.
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications:

• Prior experience working specifically with conceptual models, semantic retrieval, knowledge graphs, or multilingual NLP.
• Familiarity with diffusion-based generative models, concept embedding methods (like SONAR), or related state-of-the-art NLP techniques.
• Experience leading teams or mentoring junior engineers.

What We Offer:

• Compensation will initially include equity options, with salary negotiable following the completion of our next funding round.
• Flexible work arrangements (remote-friendly)
• Opportunity to work on cutting-edge AI technology and shape the future of knowledge mining and curation
• Collaborative environment with a focus on continuous learning and innovation
• Reach out to admin@qiri.ai incase you have any questions

If you're passionate about pioneering the next frontier of conceptual AI and want to build transformative models with real-world impact, we’d love to hear from you!