About the job

Alma shapes the Fintech landscape. We strive to serve and empower consumers and merchants by developing innovative solutions that redefine their purchase experience.

We are looking for a Machine Learning Engineer to work with our Foundation teams, which are responsible for developing our payment systems and offering the best user experience to merchants and consumers alike.

Depending on your interests and expertise, you’ll collaborate with one of these product teams:

- Consumer Experience: Focused on crafting seamless, user-friendly solutions, such as our web checkout platform and the self-service consumer portal.

- Merchant Experience: Empower merchants with self-onboarding tools and performance dashboards that provide actionable insights and transparency.

- Core Finance: Safeguard financial accuracy by managing real-time cash flow tracking and ensuring the integrity of our financial systems.

- Risk Management: Estimate the risk of funding a consumer's purchase or dealing with a merchant.

- Payment Lifecycle: Manage the entire payment lifecycle, from creation to post-purchase operations such as paying early or delaying installments.

About the mission

As a Machine Learning Engineer at Alma, you will join a team that has successfully developed critical ML solutions for our core business, including:

• Risk assessment tools for merchant onboarding and ongoing evaluation
• Customer scoring models that balance frictionless payment experiences with default minimization and client acceptance maximization
• Fraud prevention systems for both clients and merchants

While these risk-related topics remain our priority, we are now expanding our ML capabilities to other exciting areas of the business. In this role, you will:

• Contribute to the maintenance and improvement of our core risk assessment and fraud prevention models
• Collaborate on new ML initiatives across various business units, applying your skills to diverse challenges beyond risk management
• Participate in the full ML lifecycle, from data collection and preprocessing to model development, deployment, and monitoring
• Work closely with cross-functional teams to identify and implement ML opportunities that drive business value
• Help maintain a balance between risk-focused projects and new ML initiatives

About the Responsabilities

• Develop and refine ML models for risk assessment, fraud detection, and customer experience optimization
• Explore and implement ML solutions for new business areas, such as customer support automation or merchant onboarding assistance
• Contribute to the team's MLOps practices, improving model deployment and monitoring processes
• Participate in code reviews and knowledge sharing sessions within the team
• Stay informed about the latest ML research and technologies, applying new techniques to solve complex business problems

About you 

• Master's degree in Computer Science, Machine Learning, Statistics, or a related field
• Minimum 1 year of professional experience in machine learning or data science
• Strong programming skills in Python and proficiency with ML libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with natural language processing (NLP)
• Knowledge of MLOps practices and tools
• Solid understanding of ML fundamentals, including supervised and unsupervised learning algorithms, feature engineering, and model evaluation techniques
• Strong communication skills and ability to explain complex concepts to non-technical stakeholders
• Fluency in English & upper-intermediate level in French
• Nice-to-Have
  • Familiarity with cloud platforms (preferably GCP) and containerization technologies (e.g., Docker)
  • Familiarity with Generative AI (GenAI) technologies and large language models (LLMs) and their applications in enhancing productivity and decision-making processes
  • Experience interacting with graph databases
  • Familiarity with financial services, risk modeling, or fraud detection

[ML Stack: Python, FastAPI, VertexAI, BigQuery, PostgreSQL, Github, scikit-learn]