MLOps Engineer

3 tygodni temu


Maślice Wrocław Wrocław, Polska Adspective Pełny etat

We - as Adspective - are a tech company that's all about the intersection of advertising and AI. We're developing Virtual Product Placement technology. We are building a SaaS platform that'll let you seamlessly integrate advertising content into existing images and videos. Our platform uses AI and Machine Learning to automatically identify the best places in visual content for ad placement. This means that our clients can provide a personalised and engaging experience for viewers.

What's more, Adspective goes a step further by tailoring ads to viewer demographics, so they'll discover products that are tailored to their preferences.

We are seeking a skilled MLOps Engineer to join our forward-thinking team dedicated to revolutionizing video analytics and advertising through virtual product placement. Our project involves designing and scaling an AI pipeline on Azure, capable of managing and analyzing thousands of hours of video content to optimize advertising spaces and score their effectiveness dynamically.

Key Responsibilities:
  • Design, develop, and maintain scalable AI pipelines for large-scale video processing on Azure, focusing on virtual product placement and advertising effectiveness.
  • Optimize data flows and model integration across the pipeline to ensure efficient processing of video data.
  • Work closely with data scientists to automate the model lifecycle, including training, tuning, and deployment.
  • Monitor and enhance the performance and reliability of AI models in production.
  • Ensure compliance with data security and privacy standards.
  • Stay updated on new trends and technologies in AI, machine learning, and video analytics.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Data Science, or a related technical field.
  • Solid experience in MLOps, preferably with a background in video analytics or related fields.
  • Proficient in Azure cloud services and managing scalable environments for machine learning.
  • Experience with implementing automated ML workflows and dep learning models serving.
  • Strong analytical and problem-solving skills.
  • Excellent collaboration and communication abilities.

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