Machine Learning Engineer

casap; San Francisco, New York (CA, NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Casap in San Francisco is seeking a Machine Learning Engineer to accelerate how banks handle disputes and fraud. You will design and deploy models, build an orchestration layer, and collaborate with partners to continuously improve the product.

You should have 3+ years in production ML, strong programming in Python or R, and experience with TensorFlow or PyTorch. A product-minded approach and independent as well as team work are valued.

Qualifications

• 3+ years designing and deploying ML models in production.
• Strong knowledge of ML algorithms and data analysis.
• Experience building ML infrastructure from scratch in nascent environments.
• Product-minded, balancing innovation with user needs.
• Proficient in Python or R and ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Excellent problem-solving skills, able to work independently or in a team.

Responsibilities

• Develop and implement ML models to evaluate disputes and fraud.
• Create and manage an orchestration layer for multiple models.
• Collaborate with stakeholders to leverage data from partners and customers.

Skills

Python

R

ML frameworks

Data analysis

Problem solving

Independent work

Collaboration

Tools

TensorFlow

PyTorch

scikit-learn

Job description

About Casap

Casap is a Series A startup that has raised over $30M from Emergence, Lightspeed, and Primary Ventures. Based in San Francisco, the company was founded by product leaders from Robinhood and Chime. We are on a mission to change the way banks operate by automating disputes and fighting friendly fraud. People love what we've built, from everyday users to the biggest names in finance.

Casap is looking for a talented Machine Learning Engineer in San Francisco excited to supercharge how banks operate with a rapidly scaling product at the forefront of automation and Artificial Intelligence.

Responsibilities

• Develop and implement machine learning models to evaluate disputes and chargebacks and likelihood of fraud

• Create and manage an orchestration layer for multiple models, enabling automated and supervised decision-making processes

• Collaborate with stakeholders to leverage valuable data from partners and customers, ensuring a continuously learning experience and first-class user experience

Qualifications

• 3+ years of experience designing and deploying ML models in a high-scale production environment.

• Strong knowledge of machine learning algorithms and data analysis techniques.

• Enthusiastic about building ML infrastructure from scratch in a nascent environment.

• Ability to think like a product engineer, balancing technical innovation with practical application and user needs.

• Strong proficiency in programming languages like Python, R, or similar, and experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.

• Excellent problem-solving skills and the ability to work independently and in a collaborative team environment.