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Emploi > Stages > Informatique/Technologie > Etats-Unis > Détails de l'offre 

Staff Machine Learning Scientist, Intern - Summer 2025

Entreprise non montrée
Etats-Unis  Etats-Unis
Stage, Informatique/Technologie, Anglais
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Description du poste:

Company Description:

(COMPANY NAME) is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose - to uplift everyone, everywhere by being the best way to pay and be paid.
Make an impact with a purpose-driven industry leader. Join us today and experience Life at (COMPANY NAME).

Job Description:

Unleash the world scientist within you this summer! Inspired by Richard P. Feynman's maxim, "You do any problem that you can, regardless of field," we're inviting you to contribute your innovative skills in cross-industry advancement of science and humanity at (COMPANY NAME), the technology giant at the forefront of billions of global credit payments. We're calling all physical scientists to venture into our world of ML/AI.
The mission? To uncover fundamental truths hidden in the vast and largely untapped domain of Payment transactions, a realm as complex and intriguing as Physical interactions. Just as scientists construct effective models to make sense of real-world data, we strive to unearth elemental factors driving billions of transactions per day. With the rise of neural network-based deep learning in Physics, we're pioneering the use of these techniques to revolutionize global commerce.
And we're sitting on a gold mine of data and potential applications in the field of payments. As the world transitions from paper and metallic currency to digital payments, the need for solutions in credit, fraud protection, and security is accelerating. With VisaNet, the world's largest fully connected and controlled information network, we're at the forefront of this change, and your background in mathematical modelling, statistics, probability, big data handling, and problem-solving could help shape this future. With $185T in unrealized flows, the opportunity to revolutionize modes of interaction such as C2B, B2B, G2C, and more, awaits you.
Our vast data, the essential simplicity of our base problems, and the rapid advances in ML/AI, especially Generative AI, provide the perfect playground for making breakthroughs in ML/AI, Data Science, and Security. Join us in spearheading innovations in Foundational Machine Learning and leading-edge AI, with ample opportunity to drive patents and papers in top conferences and journals. This summer, turn the world of commerce into your laboratory. Apply for our internship program, and let's reshape the future together!

This position is for a Staff Machine Learning Scientist, Intern with understanding and experience in deep learning, who may be interested in applying deep learning to the world of payments:
* You can be part of a team building AI solutions used by billions of (COMPANY NAME) cardholders, pushing the boundaries and tradeoffs among accuracy, latency, throughput, and cost.
* Or you can apply the breakthroughs of transformers and high-performance computing to financial data -- (COMPANY NAME) has a unique dataset of decades of financial transactions -- with a unique dataset, we have an opportunity to create unique generative models, that no one else can.
* Or you can build tools and processes for experimentation, simulation, testing, and validation of AI models, merging advanced AI techniques with Gen AI capabilities -- this unique combination not only ensures the observability of AI models, but also enhances their interpretability, paving the way for clear and comprehensive insights.
* Or you can help create a forward-looking AI Governance solution to solve new challenges brought by Generative AI, including solutions to issues of AI fairness and explain-ability.
* Last, but not the least, you can join the efforts of synthetic data engineering which looks to create an efficient data factory running various learning and generative models for (COMPANY NAME)'s data at scale while respecting all requirements for security, compliance, and privacy.
Some job duties and projects could include
* Collaborate with the team manager of the embedded team to come up with a proposal of work that bridges Deep Learning knowledge with a problem that the team is trying to solve.
* Execute the proposal with coding and design in (COMPANY NAME)'s engineering environment and datacenters, with a demo that showcases the contribution made during the visit.
* Evangelize and grow deep learning knowledge within the team and outside based on the work.

Qualifications:

Basic Qualifications
* Students pursuing a Ph.D. with a graduation date in December 2025 or later
* Strong communications skills, specifically, the absence of repeated grammatical or typographical errors, clear and concise written and spoken communications that demonstrate professional judgment.
Preferred Qualifications
* Experience in innovative and new areas such as Machine Learning, Deep Learning, MLOps.
* Experience with hands-on development, solving a range of modeling problems, e.g Predictive Modeling, Reinforcement Learning, Large Language Models (LLMs)
* History of published papers or conference presentations on Deep Learning
* Experience in software engineering, with the ability to develop large scale and low latency infrastructure for deep learning data, modeling, and system evaluation.
* Experience in using at least one mainstream deep learning frameworks (PyTorch/TensorFlow).
* Understanding of Transformer architectures and their applications.
* Familiarity with the latest advancements in LLMs and generative AI technologies.
* Author for publications at top-ranked, peer-reviewed AI conferences/journals.
* Expertise in at least one of the following: Golang, Java, Python, or C/C++

Additional Information:

U.S. APPLICANTS ONLY: The estimated hourly range for a new hire into this position is $53.00 to $58.00 which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. (COMPANY NAME) has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.
Work Hours: Varies upon the needs of the department.
This is a hybrid position: Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.
Travel Requirements: This position requires travel 5-10% of the time.
Mental/Physical Requirements: This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.
(COMPANY NAME) is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. (COMPANY NAME) will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
(COMPANY NAME) will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code

Origine: Site web de l'entreprise
Publié: 28 Sep 2024
Type de poste: Stage
Secteur: TIC / Informatique
Langues: Anglais
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