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Senior AI/ML Engineer

172k – 238kChicago, ILNew York, NYSan Francisco, CASeattle, WAHybrid5+ YOE
Summary

Senior AI/ML Engineer building transformer and deep learning models on financial and behavioral data to power personalized growth and marketing experiences at Chime. Requires strong production ML experience with PyTorch, AWS, and large-scale data infrastructure.

About the role

Responsibilities

  • Develop and deploy sequential deep learning models and traditional machine learning systems to power growth and marketing initiatives
  • Build predictive models using large-scale financial, transactional, and behavioral datasets to improve personalization and member engagement
  • Partner cross-functionally with Growth & Marketing, Product, and Engineering teams to drive strategic AI/ML initiatives
  • Design and improve infrastructure for training, serving, and monitoring large-scale ML and deep learning systems in both batch and real-time environments
  • Generate insights and recommendations that improve growth effectiveness and the overall member experience
  • Contribute to experimentation frameworks, optimization strategies, and scalable ML platform capabilities
  • Help identify technology gaps and opportunities where AI/ML solutions can create measurable business impact

Requirements

  • Deep expertise in building sequential and deep learning models, especially outside of traditional NLP applications and within financial or behavioral data domains
  • Strong experience across the end-to-end ML lifecycle, including training, experimentation, optimization, deployment, and monitoring
  • Experience working with large-scale transactional, financial, or behavioral datasets to develop predictive models
  • Hands-on experience with AWS and modern ML infrastructure tools such as SageMaker, Kafka, Airflow, Redis, Snowflake, and Spark
  • Strong proficiency in Python, SQL, and distributed computing and model training frameworks such as PyTorch and PySpark for scalable ML development
  • A strong MLOps mindset with experience deploying and maintaining production-grade ML systems
  • The ability to operate independently, collaborate cross-functionally, and move quickly in ambiguous environments

Compensation & Benefits

  • Base salary: $172,000 - $238,000
  • Eligible for bonus, competitive equity package, and benefits
  • 401k match plus medical, dental, vision, life, and disability benefits
  • Generous vacation policy and company-wide paid days off
  • Up to 24 weeks of paid parental leave for birthing parents and 12 weeks for non-birthing parents
  • Annual wellness stipend
  • 1% of time off to support local community organizations
Skills
PythonSQLPyTorchPySparkAWSSageMakerKafkaAirflowRedisSnowflakeSparkDeep LearningMachine LearningMLOps
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