Production AI Intern: RL, LLMs & Forecasting

TWG Global AI; Santa Monica (CA); On-site; USD 62,000 - 83,000; Full time

Job summary

TWG Global is seeking a Data Science Intern on the SOLT team in Santa Monica, CA to design, build, and test production AI systems powering business workflows across a diversified portfolio.

You will gain hands-on experience in predictive modeling, time series forecasting, reinforcement learning, optimization, and LLM-powered applications while shipping real business solutions to production under supervision of experienced data scientists.

Qualifications

• Pursuing a Master’s or PhD in CS, data science, statistics, or related field.
• Experience with AI/ML including predictive modeling, time series, optimization, or reinforcement learning.
• Hands-on experience building LLM applications.
• Proficiency in Python and data libraries.
• Strong communication and teamwork.
• Experience with enterprise data platforms or cloud ML tools is a plus.

Responsibilities

• Frame questions from ambiguous business problems and ship models to production.
• Build predictive models, experimentation, optimization, and RL systems.
• Contribute to production LLM applications and evaluation.
• Prototype AI techniques and benchmark new tools.
• Do exploratory data analysis and feature engineering.
• Collaborate with stakeholders to translate requirements into tasks.
• Document work and report project performance with governance.

Skills

Python

Statistics

Analytical thinking

Team collaboration

Communication

Education

Master's or PhD in CS/Data Science/Engineering

Tools

Pandas

NumPy

scikit-learn

PyTorch

Job description

TWG Global is seeking a Data Science Intern on the SOLT team in Santa Monica, CA to design, build, and test production AI systems powering business workflows across a diversified portfolio.

You will gain hands-on experience in predictive modeling, time series forecasting, reinforcement learning, optimization, and LLM-powered applications while shipping real business solutions to production under supervision of experienced data scientists.