onsite
Lead AI Engineer - Vision Model Customization VLM - Capital One
AI Engineer
Lead the design and deployment of advanced vision‑language models, driving responsible AI solutions that enhance real‑time customer experiences. Leverage deep learning, PyTorch, and AWS to build scalable, high‑performance vision systems.
About the role
Key Responsibilities
- Architect and implement end‑to‑end vision‑language model pipelines, from data ingestion to inference, ensuring robustness and scalability.
- Collaborate with cross‑functional teams to define model requirements, evaluate performance metrics, and iterate on architecture for optimal business impact.
- Lead model training, fine‑tuning, and deployment on AWS infrastructure, optimizing for latency, throughput, and cost.
- Establish best practices for responsible AI, including bias mitigation, explainability, and compliance with regulatory standards.
- Mentor and guide a team of ML engineers and data scientists, fostering a culture of continuous learning and innovation.
Requirements
- 10+ years of experience in machine learning with a focus on computer vision and vision‑language models.
- Proficiency in Python, PyTorch/TensorFlow, and cloud platforms (AWS).
- Strong background in deep learning architectures (CNNs, transformers) and large‑scale model deployment.
- Demonstrated ability to translate business problems into technical solutions and communicate complex concepts to non‑technical stakeholders.
- Experience with responsible AI practices, including bias detection, model interpretability, and regulatory compliance.
Skills
pythonmachine learningcomputer visiondeep learningpytorchaws