TL;DR

GenAI Data Scientist (AI): Designing, building, and scaling machine learning infrastructure and GenAI applications with an accent on production-level LLM systems, RAG pipelines, and end-to-end ML solutions. Focus on optimizing performance, reliability, and integrating external APIs for business outcomes.

Location: Hybrid, Austin, TX, US. Candidates must be authorized to work in the job posting location on a full-time basis without visa sponsorship.

Salary: $68,205 - $126,668 per year

Company

%hirify_global% is a world leader in gaming content and technology, and a top-tier publisher of free-to-play mobile games, focused on delivering performance for B2B customers and joy to players.

What you will do

Develop and deploy GenAI-based applications using enterprise frameworks and custom pipelines.
Implement and optimize RAG and Agentic systems using vector search techniques.
Handle ML pipelines and infrastructure for training, inference, monitoring, and tracking.
Collaborate with Data Scientists and Machine Learning Operations to scale prototypes to production.
Work closely with data engineers and software engineers to deploy models into production systems.
Present recommendations and results clearly, tailored to the relevant audience.

Requirements

BSc in mathematics, statistics, computer science, or relevant experience (MS preferred).
Additional training and experience in Data Science, BI, Data Visualization, Analytics, Programming relevant to the gambling industry.
Strong knowledge of SQL, Python, R.
Basic understanding of version control systems (e.g., Git, GitHub).
Basic familiarity with cloud infrastructure (Azure, GCP, AWS).
Working knowledge of reporting visualization tools.

Culture & Benefits

World Leader in Gaming Entertainment.
Robust benefits package including health, dental, and vision insurance.
Paid time off and a 401(k) plan with employer matching.
Global career opportunities.
Commitment to responsible gameplay, governance, employee wellbeing, and sustainability.
Diverse and inclusive environment, valuing individual differences.