This role is for one of the Weekday's clients

Salary range: Rs 3000000 - Rs 6000000 (ie INR 30-60 LPA)

Min Experience: 5 years

Location: Bengaluru

JobType: full-timeWe are looking for a Machine Learning Engineer (Risk) to develop and implement cutting-edge machine learning solutions for complex risk-related challenges. You will analyze large datasets, detect patterns, and build scalable models to enhance fraud detection and risk assessment. This role requires a deep understanding of the machine learning lifecycle, including algorithms, data structures, and system design.

Requirements

Key Responsibilities

🔹 Develop & Optimize ML Models

• Design, develop, and implement machine learning algorithms to solve risk-related challenges.
• Leverage data-driven insights to enhance fraud detection and risk assessment capabilities.

🔹 Data Processing & Analysis

• Identify and apply appropriate techniques to process and analyze large datasets (both labeled and unlabeled).
• Extract valuable insights to improve risk models and decision-making.

🔹 System Enhancement & Performance Tuning

• Conduct performance analysis, scaling, tuning, and optimization of ML models.
• Review and enhance software and system architecture for stability and efficiency.

🔹 Cross-Functional Collaboration

• Provide technical support across different areas of the system, beyond just ML applications.
• Work closely with engineering, data, and risk teams to build scalable solutions.

🔹 Research & Development

• Explore and implement innovative approaches in fraud detection and risk modeling.
• Stay up to date with the latest advancements in machine learning, credit risk modeling, and fraud detection.

Requirements

✔ Bachelor’s degree in Computer Science, Information Systems, or related fields with a specialization in Machine Learning.
✔ Strong foundation in databases (MySQL, NoSQL, Columnar databases) and data scaling techniques.
✔ Hands-on experience with Machine Learning algorithms and their real-world applications.
✔ Proficiency in programming languages such as Python, C++, and C.
✔ Mandatory experience in Credit Risk, Unsupervised Modeling, and Fraud Modeling.
✔ Experience in the e-payments or e-commerce industry is a plus.
✔ Excellent analytical, communication, and problem-solving skills.