Job description
About the Role:The machine learning team is looking for a Senior Machine Learning Engineer to help build data-driven products using machine learning/data science. This is an opportunity to be an influencer of and a significant contributor to the direction and growth of the team. As a full-stack machine learning engineer, you will:
• Help solve a variety of problems using data to influence the experience of millions of lenders and borrowers around the world.
• Ideate, prototype, and productionize machine learning models.
• Build and scale production-ready ML and back-end infrastructure and services.
• Influence and help execute our product strategy by collaborating with product managers, business stakeholders as well as other engineers.
• Help foster a spirit of innovation and collaboration both within the team and across the organization.
• Work to create impactful and sustainable solutions to complex problems by taking bold and measured risks.
• Balance your technical excellence with a high E.Q., showing up with a sense of empathy, awareness, and responsibility.
• Share the knowledge you bring and gain generously with your peers to perpetuate a culture of engineering excellence.
About You:
• You have a BS in a quantitative discipline (computer science, engineering, physics, mathematics, or a related field) or comparable work experience.
• You have 3+ years of experience in prototyping and productionizing data and machine learning-driven products.
• You have experience in one or more of the following : - recommender systems, predictive modeling, reinforcement learning (e.g., multi-armed bandits), personalized search, computational optimization, natural language processing, deep learning, causal inference especially as applied to e-commerce/marketplaces/email marketing.
• You have experience with Docker, Kubernetes, and workflow orchestration tools (e.g. Airflow).
• You have coding skills in Python and SQL (nice to have Kotlin or Java experience).
• You have exposure to distributed systems and architectures (such as Kafka).
• You have the ability to communicate findings and recommendations to technical and non-technical audiences.
• You are willing to learn, take initiative, and wear multiple hats as required.
