Job Description Summary

We are seeking a Staff Software Engineer – ML & Computer Vision to lead the design, development, and deployment of AI/ML-powered image analytics solutions.
This role combines deep learning, computer vision, data science, and software engineering expertise to build scalable, production-grade systems for thermal analysis, corrosion detection, object detection, change detection, and other image-based analytics applications.
You will collaborate with data scientists, software engineers, and product teams to design architectures, implement ML pipelines, and deliver actionable insights for industrial and enterprise applications.

Job Description

Responsibilities & Required Skills

Machine Learning & Data Science

• Design, implement, and deploy deep learning models using PyTorch, TensorFlow, and HuggingFace Transformers.
• Work with image data, thermal imagery, corrosion inspection data, UAV/drone imagery, and multi-modal sensor data.
• Develop models for object detection, segmentation, change detection, anomaly detection, and predictive analytics.
• Build end-to-end ML pipelines: data ingestion → preprocessing → model training → deployment → monitoring.
• Apply transfer learning, CNNs, Vision Transformers, and state-of-the-art deep learning techniques.
• Conduct data exploration, feature engineering, and statistical analysis to support model development.

Computer Vision & Image Analytics

• Handle large-scale image datasets, implement preprocessing, augmentation, and efficient storage.
• Apply computer vision techniques for thermal analysis, corrosion detection, object detection, change detection, and predictive maintenance.
• Optimize models for real-time inference, edge deployment, and cloud scalability.

Full-Stack & Cloud Integration

• Integrate ML models into cloud-native SaaS platforms using AWS, GCP, or Azure.
• Build REST APIs, microservices, or SDKs to serve AI/ML models to applications.
• Deploy containerized ML solutions using Docker & Kubernetes, ensuring scalability, reliability, and security.
• Design multi-tenant SaaS architectures supporting both batch and real-time inference pipelines.

Technical Leadership

• Lead architecture and technical decisions across ML, computer vision, cloud, and full-stack systems.
• Mentor engineers and define ML/AI best practices, production standards, and observability.
• Influence platform and product strategy, ensuring AI/ML models are scalable, maintainable, and performant.
• Establish MLOps pipelines, monitoring, and model lifecycle management in production.

Required Skills

• 8+ years of professional software engineering experience, with 3+ years in ML/Computer Vision.
• Strong proficiency in Python, including PyTorch, TensorFlow, NumPy, Pandas, and SciPy.
• Hands-on experience with deep learning for computer vision: CNNs, Vision Transformers, segmentation, object detection, and change detection.
• Strong data science fundamentals: statistics, feature engineering, data preprocessing, model evaluation.
• Production deployment experience: Docker, Kubernetes, cloud platforms (AWS/GCP/Azure).
• Experience with end-to-end ML pipelines, MLOps practices, and scalable model serving.
• Knowledge of system design, distributed systems, and multi-tenant SaaS architectures.

Additional Information