wex
PhD Intern- AI/ML/NLP Engineer
Vaga remota de AI ML Engineer com fit claro de localização do candidato.
Publicada3 de jul. de 2026
Países elegíveis1 país aceito
Sinal de senioridadeJunior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Estados Unidos
Resumo da vaga
PhD Intern- AI/ML/NLP Engineer
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
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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