Software Engineer, Applied Machine Learning (Semantic Search, Natural Language Processing (NLP), Large Language Models) – Priceless Platform

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Welcome to an Exciting Career Opportunity at Mastercard!

Software Engineer, Applied Machine Learning (Semantic Search, Natural Language Processing (NLP), Large Language Models) – Priceless Platform

Our Purpose

At Mastercard, we work diligently to connect and empower an inclusive, digital economy that benefits everyone, everywhere. By making transactions safe, simple, smart, and accessible, we aim to foster growth and potential. Utilizing secure data, networks, partnerships, and a passion for innovation, we help individuals, financial institutions, governments, and businesses achieve their greatest potential. Our Decency Quotient (DQ) is the cornerstone of our culture, fostering inclusivity and respect for individual strengths, views, and experiences within our team. Embracing diversity enables us to make better decisions, drive innovation, and deliver superior business results.

Job Overview

If you have over 4 years of industry experience working on Natural Language and text-based Machine Learning technologies, such as Semantic Search, Natural Language Processing, Vector Databases, Foundation Models, or Large Language Models, we want to hear from you.

The Priceless Platform is Mastercard’s premier AWS-hosted global platform for our customers and partners. Created by a Silicon Valley startup acquired by Mastercard, we are experiencing substantial growth and are working to scale our platform. We seek to integrate additional Semantic Search and Natural Language Processing (NLP) capabilities into our platform with your expertise.

Job Summary

As a hands-on Software Engineer, you will join our team to develop and deploy Applied Machine Learning capabilities, such as Semantic Search, improved Recommendations, enhanced Text processing and Translations, and possibly a conversational interface. You will utilize ML-based Semantic Search techniques, NLP, Foundation models, and large language models (LLMs) to build and deploy these capabilities within our platform.

Responsibilities

  • Explore and apply techniques like Semantic Search to enhance and scale the search functionality in our platform, using technologies like Elastic.
  • Design and implement a scalable text processing flow to enhance our text and image content processing workflows, applying state-of-the-art NLP, Foundation, or LLM models such as GPT, Claude, Gemini, BERT, or other transformer-based architectures.
  • Prepare high-quality training data or apply retrieval augmentation models to improve system performance and accuracy.
  • Fine-tune and customize the LLM models to adapt them to specific domain requirements of our recommendation system.
  • Develop and integrate evaluation metrics to continuously monitor and enhance the performance of the recommendation engine.
  • Optimize the recommendation system for low latency, high throughput, and efficient resource utilization.
  • Stay updated with the latest advancements in ML/NLP/LLM research and incorporate relevant techniques and models into the recommendation engine.
  • Collaborate with cross-functional teams, including product managers and software engineers, to seamlessly integrate the recommendation engine into our website and applications.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
  • 4+ years of proven industry experience with Semantic Search (Elastic), NLP, large language models (LLMs), transformer architectures, and deep learning frameworks (e.g., TensorFlow, PyTorch).
  • Solid understanding of NLP techniques, including text preprocessing, embeddings, and language models.
  • Experience with retrieval augmentation models and their application in recommendation systems or related domains.
  • Strong programming skills in Python and familiarity with relevant libraries and tools (e.g., Hugging Face, NLTK, scikit-learn).
  • Knowledge of cloud computing platforms (e.g., AWS, GCP) and experience deploying and scaling AI/LLM models.
  • Excellent problem-solving, analytical, and debugging skills.
  • Ability to work collaboratively in a team environment and effectively communicate complex technical concepts.

Inclusion and Equal Opportunity

Mastercard is an inclusive, equal opportunity employer. We consider applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability, veteran status, or any other characteristic protected by law. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact and specify the type of accommodation or assistance you seek. Please do not include any