Vision Language Model Engineer (AI)

TL;DR

Vision Language Model Engineer (AI): Design, develop, and optimize advanced vision-language models integrating visual and textual data to enable intelligent systems. With an accent on multimodal AI, deep learning frameworks, and model deployment. Focus on building state-of-the-art models for image captioning, visual question answering, and text-to-image generation, optimizing for accuracy, latency, and scalability.

Location: On-site in San Francisco, United States

Company

hirify.global pioneers AI-driven infrastructure intelligence, creating living digital twins for real-time urban ecosystem insights and management.

What you will do

• Design and implement state-of-the-art vision-language models using deep learning frameworks.
• Develop and fine-tune models combining computer vision and NLP for image captioning, visual question answering, and text-to-image generation.
• Collaborate with data scientists and software engineers to integrate models into production systems.
• Optimize model performance for accuracy, latency, and scalability in real-world applications.
• Conduct experiments to evaluate and iterate on model architectures and training pipelines.
• Contribute to data preprocessing, augmentation, and annotation pipelines for multimodal datasets.

Requirements

• Must be located on-site in San Francisco, United States.
• Bachelor’s, Master’s or Ph.D. in Computer Science, Machine Learning, AI, or related field, or equivalent experience.
• 3+ years experience in machine learning focused on vision-language or multimodal AI.
• Hands-on experience with PyTorch or TensorFlow and proficiency in Python.
• Experience with large-scale model training, optimization, and cloud deployment.
• Strong communication skills to explain complex technical concepts.

Culture & Benefits

• Medical, dental, and vision coverage for US employees and dependents.
• Flexible Spending Accounts (FSA and DCFSA).
• 401(k) plan with 3% company matching.
• Unlimited paid time off.
• Profit sharing opportunities.
• Learning and development with a diverse expert peer group.