Jobs · Engineering

Senior Machine Learning Engineer

Haystack · United States · 1 mo ago
RemoteRemoteEngineeringFull-time

About the role

We are working with a leading technology solutions provider specializing in AI and machine learning, helping businesses leverage cutting-edge innovations to drive growth and efficiency.

Responsibilities

  • Design, develop, train, evaluate, and deploy production-grade machine learning and deep learning models for computer vision applications.
  • Build end-to-end machine learning pipelines covering data ingestion, preprocessing, feature engineering, model training, evaluation, deployment, monitoring, and continuous improvement.
  • Train deep neural networks on large-scale image datasets and optimize model architectures for accuracy, latency, scalability, and robustness.
  • Develop computer vision solutions for image classification, object detection, segmentation, localization, image similarity, and feature extraction.
  • Own the complete machine learning lifecycle, including experiment design, hyperparameter optimization, model versioning, reproducible training pipelines, and model performance monitoring.
  • Lead and mentor Machine Learning Engineers, Data Scientists, and Software Engineers, providing technical direction and establishing engineering best practices.

Requirements

  • Proven experience in designing, developing, and deploying machine learning and deep learning models for computer vision.
  • Strong background in building and managing end-to-end machine learning pipelines.
  • Expertise in training deep neural networks and optimizing model architectures.
  • Experience with distributed training pipelines, utilizing multiple GPUs and processing large-scale datasets.
  • Proficiency in applying model explainability techniques.
  • Collaborative mindset with experience working alongside Product Managers, Data Scientists, and other engineering teams.

Benefits

  • Opportunity to work on cutting-edge AI and machine learning projects.
  • A role with significant impact on technical direction and engineering best practices.
  • Mentorship and leadership opportunities within a dynamic team.
  • Engagement with a variety of stakeholders to deliver robust AI solutions.

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