Senior Machine Learning Scientist

We are looking for a Senior ML Scientist to design and develop next generation AI and ML models that solve real world challenges in the payments ecosystem covering transaction monitoring, fraud detection, and risk mitigation across multiple Visa businesses. You will be part of cross-functional team of data scientists and ML engineers based out of Bangalore and collaborating globally, driving innovation in the Risk and Identity Solutions (RaIS) through advanced AI/ML technologies.

You will combine deep technical expertise with ownership, velocity, and influence. You will drive the scientific roadmap at scale, ensuring models are aligned, explainable, and robust, and you ll collaborate with world class experts while influencing product strategy in a high stakes domain. The position offers access to top tier compute, tools, and datasets, and a collaborative, innovative culture focused on shaping the future of global payments.

Responsibilities:

• Extract insights from large-scale Visa datasets across business lines to define high-value, fit-for-purpose problems beyond payments - driving clarity and framing business impact with precision.
• Rapidly design, experiment, and deploy SOTA ML/AI models, owning the full lifecycle and ensuring solutions are scalable, measurable, and aligned with strategic goals.
• Lead future-forward AI/ML research, proactively identifying emerging techniques, publishing influential work, and filing patents to amplify Visa s innovation footprint.
• Integrate models into production with engineering and product teams, building robust, compliant pipelines with an eye on velocity, reliability, and business outcomes.

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.

Preferred Qualifications -

• You have 3-6 years of work experience with a Bachelor s Degree or with an Advanced degree. PhD/MS in computer science, machine learning or related field preferred.
• Strong fundamentals in machine learning, deep learning, and optimization and solid understanding of the math behind them.
• You should be able to derive algorithms from first principles and understand their limitations.
• Proven track record 3+ years of building AI / ML models which can handle scale (think model size, latency, architecture etc.,).
• You ve shipped models that matter, ideally in production environments with real users and measurable impact.
• You have deep technical and domain expertise in at least two domains where you can connect different ML techniques (e.g. contrastive learning, domain adaptation, etc.) to appropriate business problems.
• Fluency in code, you write clean, efficient Python, and you re comfortable navigating large codebases.
• You treat code as a medium for clarity and experimentation. You have experience in PySpark, PyTorch, tensor flow, as well as GPU based compute environments.
• Research mindset with product intuition. You know when to read papers and when to write them.
• You can balance novelty with practicality and know how to translate ideas into working systems.
• You are deeply technical covering both ML as well as deep learning fundamentals spanning design, pre-training, fine-tuning, and evaluation.
• Ownership and velocity. You take initiative, move fast, and iterate. You don t wait for permission, you define the problem, build the solution, and drive it to completion.
• Communication clarity. You can explain complex ideas simply, whether in a design doc, a pull request, or a hallway conversation. You write well and think clearly.