Risk Data AI/ML Engineer
SoFi
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Who we are:
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The role
We seek a highly skilled and innovative Risk Data AI/ML Engineer to design, develop, and implement advanced data, machine learning, automation, and large language model (LLM) solutions for the Credit, Collections, and Fraud domains. In this hands-on role, you will build scalable platforms, automate Risk Data operations, and deliver impactful AI/ML and LLM-driven solutions. This role is pivotal in enabling data-driven decision-making, operational efficiency, and strategic innovation across the organization.
What You'll Do
Technical Delivery and Execution
- Design, develop, and deploy AI/ML solutions to support risk management objectives across Credit, Collections, and Fraud.
- Build scalable data pipelines, platforms, and APIs to support AI/ML applications, analytics workflows, and LLM-based tools.
- Develop and implement advanced automation solutions to eliminate manual processes, enabling teams to focus on high-value initiatives.
- To enhance decision-making and operational efficiency, create AI analytics and LLM-based tools, including Retrieval-Augmented Generation (RAG) systems and intelligent agents.
- Leverage advanced machine learning techniques to provide actionable insights and improve strategies within the Decision Engine.
Collaboration and Stakeholder Engagement
- Partner with the Risk Data AI/ML Product Manager and stakeholders to understand and translate business needs into technical implementations.
- Work closely with data scientists, engineers, and business teams to ensure seamless integration of AI/ML and LLM solutions into workflows.
- Effectively communicate technical concepts, LLM capabilities, and project progress to stakeholders as required.
Operational Excellence
- Ensure the scalability, reliability, and security of data systems, AI/ML models, and LLM applications.
- Implement monitoring, logging, and performance optimization strategies for data pipelines, deployed models, and LLM-based tools.
- Maintain adherence to data governance, compliance, and security standards across all AI/ML and LLM-driven initiatives.
What you’ll need:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
- 8+ years of experience in data engineering, software engineering, or AI/ML development.
- Proven expertise in delivering AI/ML products, LLM-based solutions, and automation initiatives in financial services or similar domains.
- Strong programming skills in Python.
- Experience with Data Engineering; familiarity with Snowflake and dbt is strongly preferred.
- Experience with dbt MetricFlow is strongly preferred
- Proficiency with Airflow for building and managing data workflows.
- Familiarity with AI/ML frameworks such as TensorFlow, PyTorch, and SageMaker.
- Hands-on experience building and maintaining scalable data pipelines, APIs, and platforms.
- Expertise in cloud platforms (AWS preferred) and modern MLOps practices (e.g., CI/CD pipelines, Docker, Kubernetes).
- Practical experience with LLMs, including working with APIs, developing RAG systems, and building intelligent agents.
- Proven experience in designing and deploying advanced automation solutions.
- Strong understanding of AI/ML concepts, including model training, deployment, monitoring, and operationalization.
- Strong problem-solving and analytical skills, focusing on delivering practical, high-impact solutions.
- Effective communication skills to articulate complex technical and LLM-related concepts to technical and non-technical audiences.
- Ability to work independently and collaboratively in cross-functional teams.
