Sourceability

Sourceability

Principal Computer Vision Scientist

United States · Principal

Sponsorship not specifiedDetected 5 days ago
PythonAlgorithmsGitAzureDockerDevOpsRESTMachine LearningDeep LearningPyTorchscikit-learnPandasNumPyData AnalysisNLPComputer VisionMLOpsA/B TestingAgileSupply ChainLogisticsProcurementPerformance ManagementRobotics

About the role

  • Sourceability ® is a global digital distributor of electronic components transforming how modern businesses bring products to market.
  • This role will be responsible for research direction, model architecture, experimentation, model quality, production readiness, and practical implementation of computer vision solutions used in company products.
  • This is a senior technical leadership role for a highly experienced specialist who can work across research, engineering, product, and production systems.

Responsibilities

  • Train, fine-tune, evaluate, optimize, and deploy models for object detection, semantic segmentation, image classification, feature matching, OCR, visual search, and image understanding.
  • Build prototypes, proof-of-concepts, demos, and technical experiments to validate new ideas before full product implementation.
  • Support planning and estimation for AI / ML work by clarifying technical complexity, risks, dependencies, and realistic delivery assumptions.
  • Create technical documentation, model evaluation reports, architecture notes, and recommendations for engineering and product teams.
  • Partner with Product / Delivery Managers to translate business needs into practical AI / ML implementation plans.
  • Own the full model lifecycle, including data analysis, dataset quality, annotation requirements, model training, experiment tracking, evaluation, deployment, monitoring, and continuous improvement.
  • Partner with Engineering Managers, Team Leads / Architects, QA, DevOps, Data, and business stakeholders to make sure AI / ML work can be delivered and supported in production.
  • Sourceability is building a new Global Engineering Organization (GEO) to strengthen internal software delivery, improve production ownership, and build long-term engineering capability inside the company.
  • The right candidate should be able to evaluate new approaches, design model architectures, run experiments, improve model quality, and help engineering teams bring AI / ML capabilities into real production workflows.

Requirements

  • Strong practical experience with PyTorch and / or TensorFlow.
  • Experience with OpenCV, NumPy, Pandas, scikit-learn, and modern Python ML ecosystem.
  • Strong experience with object detection, semantic segmentation, image classification, feature matching, image retrieval, and model evaluation.
  • Experience with model optimization for inference speed, latency, memory usage, scalability, and reliability.
  • Experience with REST APIs, Docker, CI / CD, model versioning, experiment tracking, and MLOps practices.
  • Strong understanding of datasets, data quality, annotation processes, labeling requirements, and model error analysis.

Compensation

  • Engineering Managers remain responsible for hiring, performance management, compensation input, team structure, and capacity planning.

Benefits

  • We are looking for a Principal Computer Vision Scientist to lead advanced Computer Vision and AI / ML work inside GEO.
  • This role requires PhD-level education and strong hands-on experience in applied Computer Vision, Machine Learning, and Deep Learning.
  • This role will be primarily aligned with the Computer Vision product group inside GEO.
  • Lead research, design, development, and implementation of Computer Vision and AI / ML solutions.
  • Review and improve existing Computer Vision pipelines, model quality, inference performance, scalability, and production reliability.
  • Provide technical guidance and mentoring to engineers working on AI / ML and computer vision features.
  • PhD in Computer Science, Computer Vision, Machine Learning, Artificial Intelligence, Applied Mathematics, Electrical Engineering, Robotics, or closely related technical field.
  • 7+ years of hands-on experience in Machine Learning / Deep Learning, with strong focus on Computer Vision.
  • Deep understanding of classical Computer Vision algorithms and modern deep learning approaches.
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