Back to search:AI ML / Washington, Dc
Overview

We are seeking 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. The ideal candidate will have strong expertise in computer vision, deep learning, and Python-based model development, with experience deploying solutions on the Azure AI/ML stack. Experience with front-end development using React is a strong plus.


Locations: New York, Washington DC, Denver, Seattle, Los Angeles, Chicago, Austin, or Dallas.


Impact
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, TensorFlow, OpenCV, MMDetection, Detectron2, etc.

  • Apply techniques like transfer learning, fine-tuning, and model optimization (quantization, pruning).

  • Maintain reproducible experimentation using MLflow, notebooks, and versioning 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.

  • (Nice to have) Build lightweight front-end dashboards using React for visualization of image/video results.


Cross-functional Collaboration

  • Work closely with product, engineering, and domain teams to translate requirements into technical solutions.

  • Document workflows, architectures, and best practices.


Who You Are
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, TensorFlow, OpenCV, scikit‑learn, NumPy, 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, DevOps).

  • 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.


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, TensorRT).

  • Familiarity with MLOps tools (DVC, MLflow, Kubeflow).


Benefits & Compensation

  • 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.


Compensation:


Expected Salary (all locations): $97,000 - $141,350


WSP USA (and all of its U.S. companies) is an Equal Opportunity Employer Race/Age/Color/Religion/Sex/Sexual Orientation/Gender Identity/National Origin/Disability or Protected Veteran Status.


The selected candidate must be authorized to work in the United States.

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