Position: AI / ML Engineer - Image Analytics
This opportunity is for an Artificial Intelligence (AI)/Machine Learning (ML) Engineer with hands‑on experience in image, video, and LiDAR data processing to build advanced analytics and machine learning solutions. Experience with front‑end development using React is a strong plus.
This role may be based in:
New York, Washington DC, Denver, Seattle, Los Angeles, Chicago, Austin, or Dallas.
Image, Video & LiDAR Data Analytics
- Develop and optimize computer‑vision models for image classification, object detection, segmentation, OCR, and anomaly detection.
- Build pipelines for processing large‑scale video streams (real‑time or batch).
- Work with LiDAR point‑cloud data for feature extraction, 3D object detection, scene reconstruction, and spatial analytics.
- Implement preprocessing, augmentation, and feature engineering workflows for multimodal datasets.
Machine Learning & Deep Learning Development
- Design, train, evaluate, and deploy deep‑learning models using frameworks such as PyTorch, Tensor Flow, OpenCV, MM Detection, Detectron2, etc.
- Apply techniques such as transfer learning, fine‑tuning, and model optimization (quantization, pruning).
- Maintain reproducible experimentation using MLflow, notebooks, and version‑control best practices.
Azure Cloud & MLOps
- Build and deploy models on Azure Machine Learning, Azure Databricks, and Azure Cognitive Services.
- Develop scalable data pipelines using Azure Data Lake, Azure Functions, Azure Storage, Event Hubs, etc.
- Implement CI/CD workflows, containerization (Docker), and model deployment using AKS, ACI, or serverless options.
Software & API Development
- Build Python‑based microservices for model inference and data processing.
- Develop REST APIs to integrate machine‑learning models into downstream applications.
- Build lightweight front‑end dashboards using React for visualization of image/video results (optional).
Cross‑functional Collaboration
- Work closely with product, engineering, and domain teams to translate requirements into technical solutions.
- Document workflows, architectures, and best practices.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, AI/ML, or related fields.
- 5-7 years of hands‑on experience in AI/ML engineering with focus on computer vision.
- Strong proficiency in Python and popular ML/CV libraries:
- PyTorch, Tensor Flow, OpenCV, scikit‑learn
- Num Py, pandas
- Image/video processing libraries (Pillow, FFmpeg, Open3D, PCL)
- Experience with LiDAR/point‑cloud processing (Open3D, PDAL, PyTorch3D or similar).
- Experience with Azure AI/ML stack (Azure ML, Data Lake, Functions, Dev Ops).
- Solid understanding of deep‑learning architectures (CNNs, transformers for vision, 3D models).
- Experience in model evaluation, benchmarking, and optimization.
- Strong problem‑solving skills, ability to work with noisy/unstructured multimodal data.
- Travel up to 15% of the time.
- The selected candidate must be authorized to work in the United States.
Preferred Qualifications
- Experience with React.js for building simple visualization dashboards.
- Experience with multimodal AI (image + text, video + sensor data).
- Exposure to edge deployments (NVIDIA Jetson, ONNX Runtime, Tensor
RT).
- Familiarity with MLOps tools (DVC, MLflow, Kubeflow).
What We Offer
- Opportunity to work on cutting‑edge AI/ML solutions in image, video, and 3D analytics.
- Collaborative environment with strong learning and growth support.
- Exposure to enterprise‑scale Azure AI projects.
Benefits
- Health (medical, dental, vision) and disability coverage.
- Retirement savings plan.
- Paid sick leave, paid vacation, paid parental leave, and paid bereavement/voting time.
Compensation
- Expected Salary (all locations): $97,000 – $141,350 per annum.
- WSP USA reserves the right to pay more or less based on internal equity and specific geographic location.
Equal Opportunity Employer – WSP USA (and all of its U.S. companies) is an Equal Opportunity Employer regardless of race, age, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.
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