Senior Machine Learning Engineer, Payments ML Accelerator

Job description

Role Overview

A select group of U.S.-based technology companies operating at the intersection of financial infrastructure and artificial intelligence are seeking exceptional Machine Learning Engineers to join foundational ML teams. These organizations build deep learning systems that power payment products used by millions of businesses globally from fraud detection and authorization optimization to merchant intelligence and issuer analytics.

This role spans the complete ML lifecycle: research and experimentation, large-scale feature engineering, and production deployment. Engineers in this capacity are expected to move beyond point solutions, designing reusable architectures and foundation models that serve as long-term capabilities across an organization's product surface.

If you possess deep expertise in modern deep learning, LLMs, and large-scale ML systems, and are driven to create measurable impact on global financial infrastructure, this opportunity is built for you.

Core Responsibilities

Design and deploy deep learning architectures and foundation models targeting critical payment entities including merchants, issuers, and end customers

Identify high-impact ML opportunities and drive long-term roadmap strategy through well-scoped, high-leverage initiatives

Architect generalizable ML workflows enabling rapid scaling and optimized real-time online performance

Deploy ML models to production and ensure operational reliability, latency SLAs, and system stability

Experiment with cutting-edge ML solutions across industry and academia, and ideate on product applications

Evaluate emerging techniques for applicability to complex, ambiguous business problems

Partner closely with ML infrastructure teams to influence and shape new platform capabilities

Qualifications

Minimum Requirements

7+ years of industry experience in end-to-end ML development, with a strong track record of bringing ML models to production

Proficiency in Python, Scala, and Spark

Deep expertise in deep learning, LLMs, and foundation model architectures

Demonstrated comfort with ambiguity and a bias toward action in fast-moving environments

Preferred Qualifications

MS or PhD in Computer Science, Mathematics, Physics, Statistics, or directly in ML/AI

Expertise in data manipulation for analysis: querying, defining metrics, hypothesis-driven slicing and dicing of large datasets

Experience evaluating niche and upcoming ML solutions and translating research insights into engineering decisions

Background in streaming feature pipelines and backend systems integration

Compensation & Benefits

Base Salary: $212,000 $318,000 USD annually

Equity participation in high-growth technology companies

Annual performance bonus

Comprehensive medical, dental, and vision benefits

401(k) plan

Wellness stipends and professional development support

Remote-first or hybrid flexibility work from anywhere in the U.S.

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How to Apply 2 steps

Step 1: We encourage you to explore our platform at o1dmatch.com to understand how the matching process works. Use code BONUS100 for complimentary access.

Step 2: Submit your resume through Naukri with a brief note including:

- Your key technical achievements and specializations

- Any publications, patents, or open source contributions

- Why you want to work for a US company

- Your impressions of the platform after exploring it

Candidates who demonstrate understanding of the platform and have strong qualifications will be prioritized for employer matching.