Short description of the project: The AI Archive project is an initiative within the client to research, prototype, and develop internal capabilities for 3D product design and development using generative AI. The project focuses on identifying, adapting, and fine-tuning state-of-the-art 3D generative models to support client-specific use cases.
The toolchain leverages modern machine learning architectures and in-house datasets to enable AI assisted product design and engineering/creation.

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\nTasks:
\nImplementation of data preparation pipelines for model training: \n\n

Processing and preparation of multimodal data: images, segmentation masks, depth data, and 3D assets (meshes, materials, textures) tailored to the specific technical requirements of each generative AI use case.
Preparation and validation of training datasets across modalities. Validation against technical requirements and shared upfront data quality.

\nImplementation of backend services and APIs: \n\n

Development of REST APIs using Ray Serve for model inference endpoints.
Integration with SQL databases for data access, persistence, and API backing.
Deployment as standalone jobs, backend service integrations, or cloud-based execution on AWS.
Utilization of AWS services (S3, EC2, IAM) for storage, compute and permissions.
Utilization of AWS Bedrock for managed model inference and AWS agentcore for building and deploying AI agent workloads.

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\nExecution of machine learning workflows and environment configuration:\n\n

Running inference workloads using the PyTorch framework.
Independent configuration and management of Python environments and dependencies across all deployment targets.

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\nStart: ASAP
\nCapacity: full-time, 40h/week
\nDuration: till end of 2026
\nLocation: preference for 50% onsite (Herzogenaurach), if not 100% remote is also OK
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