Member of Technical Staff - Multimodal VLM/LLM Researcher

Black Forest Labs Inc.; Freiburg im Breisgau; Vor Ort; EUR 70.000 - 100.000; Vollzeit

Zusammenfassung

A leading AI labs company is seeking a Member of Technical Staff to lead research in multimodal vision-language and large language models. The role involves developing cutting-edge models, collaborating across teams, and shaping future generative AI innovations. Ideal candidates possess strong AI expertise, experience with large-scale implementations, and a passion for pushing the frontiers of AI technology.

Leistungen

Access to state-of-the-art computing resources

Collaborative, research-focused environment

Competitive compensation package

Qualifikationen

• Demonstrated expertise in training VLMs.
• Strong publication record in multimodal AI research.
• Experience with large-scale model optimization.

Aufgaben

• Run development of multimodal vision-language models.
• Collaborate with teams to scale models.
• Conduct research for innovative generative AI solutions.

Kenntnisse

Training and fine-tuning large-scale vision-language models

Proficiency in PyTorch

Experience with distributed training systems

Implementing and scaling AI models

Jobbeschreibung

Member of Technical Staff - Multimodal VLM/LLM Researcher

Join Black Forest Labs , the pioneering team behind Stable Diffusion, Stable Video Diffusion, and FLUX.1 , as we push the boundaries of generative AI. We're seeking an exceptional researcher to run cutting-edge projects in multimodal vision-language and large language models.

Key Responsibilities

• Run the development and training of state-of-the-art multimodal vision-language models within the FLUX technology stack
• Design and implement specialized fine-tuning strategies for VLMs to address specific use cases and performance requirements
• Develop and optimize LLM implementations for prompt enhancement, content moderation, and novel applications
• Drive innovation by integrating VLM/LLM capabilities into our media generation pipeline
• Conduct research to creatively combine vision and language models for enhanced generative capabilities
• Maintain cutting-edge knowledge of the latest developments in multimodal AI and LLM research
• Evaluate emerging models and architectures for potential integration into our technology stack

Technical Leadership

• Collaborate with cross-functional teams to implement and deploy models at scale
• Contribute to architectural decisions and technical roadmap planning
• Document and share research findings with the broader team

Required Qualifications

• Demonstrated expertise in training and fine-tuning large-scale vision-language models
• Strong publication record or practical experience with relevant projects in multimodal AI research
• Proficiency in PyTorch or similar deep learning frameworks
• Experience with distributed training systems and large-scale model optimization
• Track record of implementing and scaling AI models in production environments

Nice to have

• Experience with diffusion models and generative AI architectures alongside autoregressive modelling
• Background in computer vision
• Contributions to open-source AI projects
• Experience working in fast-paced startup environments
• Strong software engineering practices and system design skills
• Experience in open-source VLM inference frameworks such as vLLM

What We Offer

• Opportunity to work with the strong technical team at Black Forest Labs
• Access to state-of-the-art computing resources
• Collaborative, research-focused environment
• Competitive compensation package
• Chance to shape the future of generative AI

We're looking for self-motivated individuals who are passionate about advancing the field of AI and can thrive in a fast-paced, research-driven environment. If you're excited about pushing the boundaries of what's possible in generative AI, we want to hear from you.

Apply for this job

*

indicates a required field

First Name *

Last Name *

Email *

Phone

Resume/CV *

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf