Senior ML 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 ML Engineer based in India. Join an innovative engineering team building next-generation infrastructure for global payments, helping businesses simplify payment operations and improve transaction performance. As a Senior ML Engineer, you will be among the first specialists shaping the organization's machine learning capabilities, working closely with experienced engineers and cross-functional partners to turn promising ideas into production-ready solutions. You will own the full machine learning lifecycle, from researching approaches and evaluating models to deployment, monitoring, and continuous improvement. Your work will help optimize payment routing decisions, improve operational efficiency, and deliver measurable business outcomes. This remote-first opportunity offers significant technical ownership, room to experiment, and the chance to establish reliable machine learning practices in an evolving environment. You will also mentor colleagues, influence technical direction, and help identify where machine learning can create the greatest impact. Accountabilities: You will lead the development and productionization of machine learning solutions, collaborating with engineering, product, and data teams to deliver reliable, measurable improvements across payment workflows. - Own the machine learning lifecycle: Research, test, train, deploy, and monitor ML-powered features, taking responsibility for their performance and reliability in production. - Optimize payment routing: Develop and productionize intelligent routing decisions across payment flows, building the infrastructure required to support scalable and dependable ML solutions. - Build production-ready ML systems: Establish and improve model versioning, CI/CD workflows, observability, monitoring, and other MLOps practices needed for reliable deployment and maintenance.

- Collaborate across teams: Work closely with product managers, data specialists, and software engineers to identify valuable use cases and translate them into shipped features with measurable outcomes. - Design and evaluate experiments: Apply statistical reasoning, experimentation, and A/B testing to validate hypotheses, assess model performance, and guide data-driven decisions. - Prioritize practical impact: Evaluate alternative approaches pragmatically, balancing model sophistication, implementation complexity, business value, and operational reliability. - Mentor engineering colleagues: Share ML knowledge, explain technical trade-offs, and help other engineers adopt machine learning techniques effectively. - Engage with customers: Speak directly with customers to validate ideas, understand real-world requirements, and ensure solutions address practical needs. - Shape technical direction: Help prioritize promising use cases, influence engineering decisions, and establish repeatable patterns and practices for future ML initiatives. Requirements: You are an experienced machine learning professional with strong software engineering foundations, statistical thinking, and the ability to independently bring models into production. You are comfortable working in an evolving environment where priorities and processes are still taking shape. - Relevant experience: Senior-level experience in machine learning engineering, data science, or applied research, with a demonstrated track record of deploying models into production through APIs, batch processing, or streaming systems. - Python proficiency: Strong Python programming skills and hands-on experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch, or Keras. - Statistics and experimentation: Ability to design and run experiments and A/B tests, interpret statistical results, and communicate clearly what the evidence does and does not demonstrate.