about 3 hours ago
Base Salary
$172k - $238k/yr
Responsibilities
- Develop and deploy sequential deep learning models and traditional machine learning systems for growth and marketing.
- Build predictive models using large-scale financial, transactional, and behavioral datasets.
- Collaborate with Growth & Marketing, Product, and Engineering teams on AI/ML initiatives.
- Design and enhance infrastructure for training and monitoring large-scale ML systems.
- Generate insights and recommendations to improve growth effectiveness and member experience.
- Contribute to experimentation frameworks and scalable ML platform capabilities.
- Identify technology gaps and opportunities for AI/ML solutions.
Requirements
- Deep expertise in building sequential and deep learning models, particularly in financial or behavioral data domains.
- Strong experience across the end-to-end ML lifecycle, including training and deployment.
- Experience with large-scale transactional, financial, or behavioral datasets.
- Hands-on experience with AWS and modern ML infrastructure tools like SageMaker and Spark.
- Proficiency in Python, SQL, and distributed computing frameworks such as PyTorch.
- An MLOps mindset with experience in deploying production-grade ML systems.
- Ability to work independently and collaborate in ambiguous environments.
Benefits
- In-office work policy with flexible remote options and team events.
- In-office perks including backup care and subsidized commuter benefits.
- Competitive salary based on experience.
- 401k match and comprehensive medical, dental, vision, life, and disability benefits.
- Generous vacation policy and company-wide paid days off.
- 1% of time off to support local community organizations.
- Annual wellness stipend for eligible expenses.
- Up to 24 weeks of paid parental leave for birthing parents.
- Access to family planning tools with significant reimbursement options.
- Engaging in-person and virtual events for team bonding.