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Machine Learning Engineer

Responsibilities

  • Use statistical and machine learning techniques to create scalable solutions for vehicle telemetry data and video analysis, and perform R&D to drive discovery of new generation mobility products
  • Establish scalable, efficient, automated processes for large scale data analysis, model development, model validation and model implementation
  • Drive adoption of best practices across organizations
  • Deliver production-ready code
  • Work with Product Owners to define the KPIs for machine learning projects
  • Stay abreast of developments in research methodology and changing technologies in the marketplace and proactively identify applications of these latest developments to improve existing methods
  • Prepare and present findings to both technical and non-technical audiences
  • Work within the constraints of time, budget, and resources capacities to align with Toyota’s global vision
  • Develop and foster collaborative relationships with product, business, and engineering teams to effectively serve our customer needs

Qualifications

  • 5+ years of production experience working in Data Science or Software Engineering
  • 3+ years of production experience in Deep Learning – Computer Vision
  • Solid production experience using Python (including NumPy) and SQL
  • Solid production experience using TensorFlow and/or PyTorch
  • Production experience with Apache Spark
  • Experience implementing solutions for video and image segmentation, object detection and tracking, and/or semantic/instance segmentation
  • Strong fundamentals in problem solving, algorithm design and complexity analysis
  • Experience implementing and orchestrating Machine Learning pipelines in production environments, using tools such as Kubeflow, airflow, Pachyderm, mlflow, etc.
  • Hands-on experience with web APIs, containers, Kubernetes, CI/CD and testing
  • Experience from working in Agile Scrum environments
  • Experience implementing solutions in a cloud environment (AWS, Azure, or Google Cloud)
  • Experience using Infrastructure-as-code for cloud infrastructure automation
  • Experience working with data science in automotive telematics data and video is a plus
  • Experience in edge computing is a plus

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