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Machine Learning Engineer

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Machine Learning Engineer in USA

  • South San Francisco, CA

Responsibilities

  • Design ML models and large-scale ML systems for underwriting and portfolio management subject to business, risk, regulatory, and engineering constraints.
  • Design systems that accelerate the development and deployment of new models.
  • Experiment and iterate on ML models using tools including PyTorch and TensorFlow.
  • Develop automated pipelines to train and evaluate models in offline and online environments.
  • Integrate ML models into production systems and ensure scalability and reliability.
  • Collaborate with product and strategy partners to propose, prioritize, and implement product features.
  • Evaluate emerging ML and AI developments and turn innovative ideas into production solutions.

Requirements

  • Bachelor’s degree or foreign equivalent in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field.
  • At least two years of experience building and shipping ML systems in production.
  • At least two years of experience with ML algorithms and model architectures, designing, training, and evaluating models, productionizing and deploying models at scale, orchestrating data pipelines and leveraging large-scale datasets, and solving business problems with deployed ML models.
  • At least one year of experience with ML libraries and frameworks including PyTorch, TensorFlow, XGBoost, or Spark.
  • At least one year of experience with deep learning, including transformers, test-time compute, or reinforcement learning.

Benefits

  • 40 hours per week
  • 50% telecommuting permitted
  • Multiple positions available
  • Equity, company bonus or applicable sales commissions/bonuses
  • 401(k) plan
  • Medical, dental, and vision benefits
  • Wellness stipends

Salary: $212k - $318k/yr

Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities.

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