Senior Machine Learning Engineer in भारत

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Machine Learning Engineer based in India. The Senior Machine Learning Engineer will help build and shape a new machine learning function within a remote-first payments technology environment. Working closely with engineering leadership and an experienced Staff Engineer, you will establish the foundations for applying machine learning to real-world payment challenges. Your primary focus will be developing intelligent payment routing solutions that improve transaction performance and deliver measurable business outcomes. You will own the complete machine learning lifecycle, from researching and testing approaches to deploying, monitoring, and optimizing models in production. Collaborating with product, data, engineering, and customers, you will identify valuable use cases and turn experimentation into reliable, scalable features. This is an opportunity to influence technical direction, establish best practices, and make meaningful contributions in a growing organization where initiative and independent problem-solving are essential. Accountabilities: As a Senior Machine Learning Engineer, you will take ownership of machine learning initiatives from initial exploration through production deployment and continuous improvement. You will work across teams to identify opportunities, evaluate solutions, and establish reliable practices that make machine learning an effective part of the payment infrastructure. - End-to-End Machine Learning Development: Own the full lifecycle of machine learning features, including research, experimentation, model training, deployment, monitoring, and ongoing optimization.

- Intelligent Payment Routing: Develop and productionize machine learning models that improve payment routing decisions, helping optimize transaction performance and payment outcomes. - ML Infrastructure and MLOps: Build and improve the infrastructure required to operate models reliably, including model versioning, CI/CD pipelines, observability, and production monitoring. - Experimentation and Evaluation: Design and run experiments, including A/B tests, to evaluate model performance and determine whether proposed solutions deliver measurable improvements. - Cross-Functional Collaboration: Partner with product, data, and engineering teams to identify valuable machine learning use cases and translate promising ideas into shipped, measurable features. - Customer Engagement: Speak directly with customers to validate assumptions, understand real-world requirements, and assess how machine learning solutions perform in practice. - Technical Direction: Help define priorities, evaluate technical trade-offs, and determine which machine learning opportunities offer the greatest potential impact. - Engineering Mentorship: Support and mentor engineers adopting machine learning techniques, sharing knowledge about experimentation, model evaluation, and practical implementation decisions. - Standards and Best Practices: Establish repeatable patterns and engineering practices that improve the reliability, maintainability, and scalability of machine learning solutions. - Continuous Improvement: Take a pragmatic, impact-driven approach to model selection and optimization, prioritizing effective solutions over unnecessary complexity. Requirements: The ideal candidate has senior-level experience in machine learning engineering, data science, or applied research, with a proven ability to take models beyond experimentation and into production. You should combine strong Python and statistical skills with sound software engineering judgment, cloud experience, and the independence needed to operate in an evolving technical environment.