ML Engineer

AI overview

Lead the development of the full machine learning stack for an innovative AI platform focused on data spend optimization, enhancing business processes through advanced ML models.
About Revefi Founded in 2021 by Sanjay Agrawal and Shashank Gupta, the visionary co-founders of ThoughtSpot ($4.2B+ valuation), Revefi is building an AI Agent for Data Spend Optimization, unifying observability across data quality, usage, spend, and performance — a category-defining platform for modern data teams. Backed by $20M in Series A funding from Icon Ventures, Mayfield Fund, GTM Capital, and StepStone Group, we’re on a mission to build the future of Data Spend Optimization and Cloud Data Operations.   The Role This is a unique, zero to one opportunity. You will be responsible for the full ML stack for the product. Responsibilities
  • Develop and implement machine learning models that can improve business processes and outcomes, including those related to anomaly detection and time series forecasting.
  • Participate in the design, development, testing, and deployment of machine learning algorithms and models.
  • Responsible for the full development and production ML stack.
  • Requirements
  • Bachelor's degree in computer science, data science or a related field.
  • 5+ years of experience in implementing, deploying and maintaining ML models.
  • Strong hands on experience in machine learning algorithms and techniques, such as regression, classification, clustering, deep learning, anomaly detection, and time series forecasting.
  • Strong programming skills in languages such as Python, Java, or R, with experience in libraries and frameworks such as TensorFlow, PyTorch, and Scikit-learn.
  • Familiarity with data analysis and visualization tools, such as Pandas, NumPy, and Matplotlib, with experience in time series analysis and visualization.
  • Excellent problem-solving and analytical skills, as well as attention to detail.
  • Good communication and collaboration skills, and the ability to work in a team environment.
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