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Senior Machine Learning Engineer

Talener

2.9
5 reviews
Talener
Job Type   /   Job Level
Full-time   /   Others/Any
Company Location
United States of America
Our client’s leading segmentation and AI-driven matching technologies help consumers find better solutions and brands faster. Their campaign-results-driven matching decision engines and optimization algorithms are built from over 20 years and billions of dollars of online media experience.

They are seeking a Machine Learning Engineer to join their team on a full-time basis. In this role, you will design, develop, and deploy machine learning models and algorithms to enhance digital performance marketing platforms. You’ll collaborate with cross-functional teams to solve complex problems and deliver scalable solutions.

Job Title: Machine Learning Engineer

Location: Fully Remote. Candidates must be in the United States to be considered.

Required Technology & Skills

  • Master’s degree in computer science, Machine Learning, Data Science, or a related field.
  • 2+ years in machine learning, data analysis, or a related role
  • Proficiency in programming languages such as Python or Scala
  • Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn
  • Strong understanding of algorithms, data structures, and statistical methods
  • Excellent problem-solving skills, and an analytical mindset
  • Familiarity with cloud technologies (AWS, GCP, Azure)
  • Familiarity with containerization tools such as Docker or Kubernetes

Additional Skills

  • Experience in digital marketing or ad tech industries
  • Knowledge of natural language processing (NLP) and recommender systems
  • Excellent written and verbal communication skills

Benefits/Perks

  • Comprehensive Benefits Package (health, dental, vision)
  • Opportunities for professional growth and development
  • Dynamic and inclusive workplace culture
  • Quarterly visits to their Foster City, CA location
  • Annual Bonus
  • Equity

Compensation: $170-220k base salary, depending on experience.

Additional Information: For additional information or to apply, please contact Brian Samela at [email protected]
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