Staff Software Engineer

Job description

Job Description

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

Relocation Assistance Provided: Yes