Role overview

Senior Machine Learning Engineer

Requirements and responsibilities

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Key Responsibilities

  • Develop and refine features for deep learning models, working with large-scale customer and behavioral datasets
  • Implement model architecture changes informed by recent academic research (e.g., papers from NeurIPS and similar venues)
  • Collaborate with client teams to understand business context and translate requirements into technical solutions
  • Optimize model training pipelines for efficiency and scalability
  • Document approaches, findings, and technical decisions for knowledge sharing across teams
  • Participate in code reviews and contribute to engineering best practices

Required Skills & Experience

  • Strong proficiency with a deep learning framework (e.g. Pytorch, tensorflow)
  • Hands-on experience with feature engineering for predictive models
  • Solid foundation in machine learning fundamentals (supervised learning, neural network architectures, optimization)
  • Ability to read, understand, and implement techniques from ML research papers
  • Python proficiency in a data science/ML context
  • Comfortable working in ambiguous environments and adapting to unfamiliar tooling

Nice to haves

  • Experience with time-series or sequential modeling
  • MLOps experience (model deployment, monitoring, pipeline orchestration)
  • Familiarity with Google Cloud Platform or large-scale distributed training
  • Background in causal inference or attribution modeling
  • Experience working in consulting or client-facing technical role
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Browse stack
FocusMachine Learning EngineeringRole area
Seniority signalSeniorCandidate level
StackPythonPrimary skills
Location1 accepted countryEligibility

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