- Build cutting-edge models Develop and deploy large language and generative models for multimodal document processing and structured data extraction.

- Innovate across modalities Explore new ways to combine text, images, and 3D data to unlock smarter, faster solutions.

- Engineer at scale Create data pipelines and training workflows that can handle massive, complex datasets.

- Deploy in the cloud Use AWS and other platforms to train, optimize, and deploy models into production at scale.

- Collaborate widely Work with engineers, product leaders, and business teams to bring AI solutions into real products and customer workflows.

- Mentor and grow Guide teammates on advanced ML methods, model architecture, and best practices, elevating the entire team.

- Stay ahead Keep up with the latest generative AI and deep learning research, and bring fresh ideas into production.

Preferred candidate profile :

- Bachelors degree required; advanced degree (M.S. or PhD) in Computer Science, Machine Learning, AI, or related field is a big plus.

- 5+ years of experience in machine learning or data science, with deep expertise in generative models, LLMs, or computer vision.

- Strong track record working with large-scale language and vision models (Transformers, GPT, VLMs).

- Hands-on experience with multimodal data (text, images, 3D).

- Proficiency in Python and key ML libraries (PyTorch, TensorFlow, pandas, NumPy).

- Solid grounding in probability, statistics, and optimization for generative modeling.

- Experience deploying ML and AI models using cloud microservice architecture (AWS preferred).

- Strong software engineering skills, including object oriented programming, testing, version control, CI/CD best practices and IaC (terraform preferred).

- A proven ability to communicate effectively with all levels of the organization, from executives to product managers and various stakeholders.

- Background in manufacturing, supply chain, or related industries is a plus but curiosity and drive matter more.