GenAI Research Scientist

Job Description

Work with Python scripts to access and integrate GenAI capabilities.

Apply agentic AI approaches to automate and optimize workflows.

Handle day-to-day tasks such as:

Taking raw data and making repositories functional on that data.

Iterating through experiments, critiquing results, and proposing alternative approaches.

Scaling scope from small tasks to full project ownership.

Break down existing processes and identify opportunities for improvement.

Collaborate with stakeholders and communicate technical concepts clearly.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

Required Skills

GenAI familiarity: Comfortable working with LLMs and related frameworks.

Python proficiency: Ability to write and adapt scripts for AI workflows.

ML fundamentals: Solid grounding in classic ML concepts to avoid common pitfalls.

Data handling: Strong experience with Pandas and managing substantial datasets.

Cloud experience: Familiarity with Azure is a plus.

Ability to run experiments, critique outcomes, and iterate effectively. Experience with agentic AI frameworks.

Broader exposure to ML beyond LLMs.

Comfort with growing scope and taking ownership of projects.