C
AI Engineer
City Detect
- Location
- Remote (City Detect (AL), California · City Detect (DAL), California · City Detect (CA), California)
- Employment
- Full-time
- Level
- Mid Level
Posted 2 weeks ago
About the Role
City Detect is seeking an AI Engineer to advance their products beyond traditional object detection using cutting-edge AI models. This role involves fine-tuning, deploying, and maintaining multi-modal models to create intelligent, scalable solutions.
Skills
Transformers
Generative Models
Vision-Language Models
Python
PyTorch
TensorFlow
LLMs
Computer Vision
Prompt Engineering
RAG Architectures
Model Quantization
Object Detection
Transfer Learning
Attention Mechanisms
Tokenization
Inference Optimization
Full job details
We're seeking an AI Engineer with deep experience in transformers, generative models, and vision-language models (VLMs) to push City Detect's products beyond traditional object detection. You'll fine-tune, deploy, and maintain multi-modal models that combine visual and language understanding to deliver intelligent, scalable solutions across heterogeneous real-world environments.
What You'll Do
- Fine-tune and deploy vision-language models (VLMs) and large language models for production use cases
- Design and maintain end-to-end pipelines for multi-modal model training, evaluation, and inference in Python
- Develop prompt engineering strategies, RAG architectures, and other techniques to maximize model performance
- Evaluate model outputs systematically and build feedback loops for continuous improvement
- Quantize large transformer models to improve model efficiency
- Stay current with rapid advances in transformer architectures, fine-tuning methods, and multi-modal research
Requirements
- 3+ years of professional experience working with transformer-based architectures
- 2+ years of hands-on experience fine-tuning and deploying multi-modal models (VLMs)
- 2+ years of proven computer vision experience, with a strong preference for object detection
- Strong experience with LLMs — fine-tuning, inference optimization, and production deployment
- Proficiency in Python for model development, training, and deployment (2+ years)
- Experience with deep learning frameworks such as PyTorch or TensorFlow
- Solid understanding of attention mechanisms, tokenization, transfer learning, and generative model fundamentals
- Proven experience taking models from experimentation through production-ready deployment
Nice to Have
- SQL proficiency for querying detection results, labeling metrics, or model performance data
- Experience with roadside or infrastructure object detection (signs, signals, debris, pavement markings)
- Background in GovTech, public sector, or smart city projects
- Experience in automated driving, ADAS, or autonomous vehicle perception systems
- Familiarity with model-assisted labeling, active learning, or human-in-the-loop workflows
- Experience with edge deployment or model optimization (TensorRT, ONNX, quantization)