Staff Machine Learning Engineer

Engineer

Staff Machine Learning Engineer

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  • Date posted
    July 15, 2026
  • Expiration date
    October 15, 2026
  • Application ends
    October 15, 2026

Our Client Currently looking for Staff Machine Learning Engineer

Responsibilities

  • Work with AI scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
  • Build “machine learning ready” feature pipelines.
  • Partner with AI scientists to understand, implement, refine and design machine learning and other algorithms.
  • Run regular A/B tests, gather data, and draw conclusions on the impact of your models.
  • Monitor and maintain production models.
  • Work cross functionally with product managers, AI scientists and product engineers, and communicate results to peers and leaders.
  • Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.

 

Qualifications

  • BS, MS, or PhD degree in Computer Science or related field, or equivalent work experience.
  • 7+ years of experience
  • Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
  • Knowledge of machine learning techniques (i.e. classification, regression, and clustering).
  • Understand machine learning principles (training, validation, etc.)
  • Knowledge of data query and data processing tools (i.e. SQL)
  • Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
  • Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
  • Experience deploying highly scalable software supporting millions or more users
  • Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
  • Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
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