ML Engineer

About the Role

Join an Engineering company, where we are developing a groundbreaking AI-driven credit advisory platform designed to provide personalized financial guidance. Our dedicated team of professionals is focused on creating robust and intelligent AI systems that facilitate real financial decisions for users. As we expand our reach to millions of users, this role offers significant growth opportunities and the chance to make a real impact in the financial technology sector.

Responsibilities

• Design and implement machine learning models to predict various financial outcomes.
• Develop and optimize data pipelines for efficient processing of large datasets.
• Collaborate with cross-functional teams to integrate AI solutions into existing systems.
• Conduct rigorous offline and online model evaluations to ensure robust performance.
• Debug and resolve model quality issues in production environments.
• Monitor and optimize model serving frameworks for scalability and efficiency.
• Stay updated with the latest technologies and methodologies in machine learning.

Requirements

• At least 3-5 years of experience in building and deploying machine learning models in production environments.
• Hands-on experience with training and fine-tuning models using PyTorch or TensorFlow.
• Demonstrated expertise in feature engineering and managing data pipelines for structured data.
• Familiarity with model serving frameworks like Triton, TorchServe, or TensorFlow Serving.
• Proficiency in optimizing models through methods including batching, quantization, and distillation.
• Experience with MLOps tools for effective experiment tracking and CI/CD processes.
• Prior experience in creating models for predicting real-world financial outcomes.

Nice to Have

• +Experience in credit, lending, or fraud detection domains.
• +Knowledge of LLM fine-tuning techniques such as LoRA or PEFT.
• +Understanding of model bias, fairness, and explainability principles in financial contexts.