wex
PhD Intern- AI/ML/NLP Engineer
Remote AI ML Engineer role with clear candidate location fit.
PostedJul 3, 2026
Eligible countries1 accepted country
Seniority signalJunior
Work settingRemote
Accepted candidate locations
USA
Role overview
PhD Intern- AI/ML/NLP Engineer
Requirements and responsibilities
Readable role content extracted into sections for faster review.
How you'll make an impact:
- 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.
Experience you'll bring:
- 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.
Preferred Skills:
- 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.
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