SITE Technologies is seeking an experienced Lead AI Engineer to join our team, focusing on computer vision and MLOps. The ideal candidate will have a strong background in both traditional image processing techniques and deep learning computer vision models, as well as experience in deploying and managing AI models in production environments.

Responsibilities:

- Lead a small team of AI engineers, providing technical guidance and mentorship

- Design and implement computer vision solutions using both traditional image processing

approaches and modern deep learning models

- Deploy AI models as both long-running processing jobs and low-latency endpoints

- Implement MLOps best practices for model deployment, monitoring, and maintenance

- Collaborate with cross-functional teams to integrate AI solutions into existing products

and workflows

- Stay up-to-date with the latest advancements in computer vision and MLOps, and apply

them to improve our systems

Requirements:

- 5+ years of experience in AI/ML engineering, with a focus on computer vision

- Experience leading small teams and mentoring junior engineers

- Strong proficiency in Python, PyTorch, OpenCV, and other computer vision libraries

- Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or similar

platforms

- Experience with containerization (Docker) and orchestration (AWS ECS, Kubernetes) for

ML workloads

- Deep knowledge of AWS services relevant to ML and computer vision, such as

SageMaker, EC2, S3, and Lambda

- Proven experience with data annotation for computer vision tasks, including use of

open-source tools or commercial solutions in a professional environment

- Experience with version control systems (e.g., Git) and collaborative development

workflows

- Strong communication skills and ability to explain complex technical concepts to

non-technical stakeholders

Preferred Qualifications:

- Advanced degree (M.S. or Ph.D.) in Computer Science, Machine Learning, or a related

field

- Contributions to open-source projects or research publications in computer vision or

MLOps

- Publications in peer-reviewed journals or conferences in the fields of computer vision,

machine learning, or related areas

- Experience with additional ML frameworks such as TensorFlow or JAX

- Familiarity with ONNX for model interoperability and optimization

- Experience with Infrastructure as Code (preferably Terraform)