AI Engineer (Remote) P.HD Candidates Only

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AI Engineer (Remote) P.HD Candidates Only

Job Summary

We are looking for a highly motivated and skilled Data Scientist with a strong background in deep learning, natural language processing (NLP) and/or computer vision to join our team. In this role, you will be responsible for development/deployment of both computer vision and vision language models (VLMs), while also contributing to the design and implementation of a cutting-edge multi-agent LLM system.

Key Responsibilities:

Develop and optimize advanced computer vision models for a range of real-world applications.

Fine-tune and deploy large language models (LLMs) using domain-specific datasets.

Design and implement scalable frameworks for multi-agent LLM collaboration and interaction.

Work cross-functionally with research, product, and engineering teams to deliver robust, ML-powered solutions.

Conduct rigorous experiments, analyze performance metrics, and iterate on model improvements.

Stay informed on the latest advancements in AI, particularly in vision, NLP, and agent-based systems.

Qualifications:

• Master s or Ph.D. in Computer Science, Machine Learning, or a related field; Ph.D. preferred.
• Extensive hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.
• Demonstrated expertise in building and training computer vision models (e.g., CNNs, Vision Transformers).
• Practical experience fine-tuning and deploying large language models (e.g., GPT, DeepSeek, LLaMA, Mistral).
• Familiarity with multi-agent systems, reinforcement learning, or AI planning is a strong plus.
• Proficient in Python with experience in designing machine learning pipelines and working with cloud-based platforms. Hands-on experience with deploying ML systems on AWS using tools like AWS CDK, Docker, and related DevOps practices.

Strong analytical and problem-solving skills with the ability to work independently and in collaborative environments.

Preferred Qualifications:

• Strong understanding of vision-language models and transformer-based architectures.
• Proven experience training state-of-the-art VLMs (e.g., CLIP, BLIP, Flamingo, LLaVA) on both domain-specific and large-scale datasets.
• Familiarity with multi-agent systems architecture and design principles.
• Experience deploying machine learning models in cloud environments, particularly using AWS services (e.g., SageMaker, EC2, Lambda).