NielsenIQ

Principal ML Engineer

NielsenIQ
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2 days ago
Remote, India or Pune, IndiaStaff+

Responsibilities

  • Design scalable software solutions focused on quality, performance, and maintainability.
  • Lead software architecture decisions and ensure alignment with business requirements and technical standards.
  • Design MLOps pipelines and coordinate software delivery with Research Leads and Product Owners.
  • Create and maintain documentation for team initiatives.
  • Collaborate with experienced and junior developers to deliver assigned solutions.
  • Perform code reviews, mentor developers, and promote software engineering best practices.
  • Own the technical debt of supported systems.
  • Lead discovery of new technologies and techniques relevant to company and project needs.

Requirements

  • 8+ years of professional experience in software development.
  • Proven experience leading machine learning-based systems.
  • Strong software engineering principles, software architecture, and object-oriented programming fundamentals.
  • Proficiency designing software architecture and data pipelines.
  • Familiarity with Azure, AWS, or GCP cloud services.
  • Experience working in Agile/Scrum environments; SAFe is a plus.
  • Strong written and verbal English communication skills.
  • Knowledge of testing frameworks and test automation using Python.
  • Preferred experience with Python and machine learning projects such as computer vision or natural language processing.
  • Preferred experience with CI/CD pipelines, GitHub Actions, and DevOps practices.
  • Preferred experience with data transformations using pandas, Spark, Arrow, or Databricks.
  • Preferred experience serving models with GPUs using CUDA, Triton, dynamic or continuous batching, LLMs, or other deep learning models.

Benefits

  • Competitive salary based on experience and skills.
  • Flexible working hours and a flexible working environment.
  • Possibility of remote work.
  • Career growth and professional development opportunities.
  • Collaborative and inclusive work environment.
  • Volunteer time off.
  • LinkedIn Learning.
  • Employee Assistance Program (EAP).

Tech Stack

Categories

Data EngineeringML Engineering
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