NLP Engineer

WEX•California, MD

10d•$35 - $43•Onsite

About The Position

As a PhD Research Intern, you will apply your deep technical expertise to solve complex, real-world problems. You are a highly motivated researcher with a passion for applying cutting-edge AI, Machine Learning, and software engineering to create tangible business value. This is a project-based internship. You will be paired with a dedicated mentor and given a high-impact project to own, from research and design through to a functional prototype.

Requirements

Currently enrolled in a PhD program in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
Demonstrated research experience in AI, Machine Learning, Deep Learning, or Generative AI (e.g., publications, conference papers, or significant project work).
Strong programming skills in at least one of our core languages: Python, Java, C#, or GoLang.
Deep understanding of modern ML algorithms, platforms, and packages (including deep learning and LLMs).
Solid grasp of probability and statistics concepts (e.g., distributions, Bayesian inference, maximum likelihood estimation).
A collaborative mindset and strong communication skills, with an ability to translate complex research into practical applications.
Evidence of innovative problem-solving and a drive to learn and excel.

Nice To Haves

Experience with cloud platforms (e.g., AWS).
Familiarity with software development best practices (SDLC), CI/CD tools, and IaC (e.g., Terraform).
Familiarity with container orchestration (e.g., Kubernetes).
Experience or interest in the financial technology (FinTech) industry.

Responsibilities

Collaborate with senior engineers, product managers, and domain experts to understand our customers' needs and challenges.
Apply your research skills to design, code, and test novel AI/ML solutions.
Develop, evaluate, and iterate on AI/ML models (including LLMs) to solve a core business problem.
Analyze existing platforms to identify bottlenecks and propose opportunities for algorithmic or systems-level improvements.
Gain hands-on experience with our production systems, including CI/CD pipelines (GitHub Actions) and Infrastructure as Code (Terraform).
Present your findings and project outcomes to the team and key stakeholders at the end of your internship.