Responsibilities
- Work extensively on our Multi‑Agent AI Analytics System, expanding capabilities to deliver conversational insights at scale.
- Design and iterate on ML models powering real‑time personalization, matchmaking, and churn prediction.
- Drive experimentation that boosts engagement, retention, and monetization through user‑level intelligence.
- Monitor real‑time data pipelines that feed anomaly detection, feature stores, and matchmaking services.
- Optimize and benchmark ML inference for live gameplay scenarios (spin‑the‑wheel rewards, sticker recommendations, GBM matchmaking).
- Partner with product, backend, and design to turn insights into delightful player experiences.
- Champion AI‑driven tooling and workflow automation across the team.
Requirements
- Final‑year B.Tech/M.S. student or recent graduate in CS, IT, Math, Stats, or related field
- Solid programming abilities in Python with the ML/AI stack (NumPy, Pandas, Scikit‑Learn, TensorFlow)
- Good grasp of Data Structures, Algorithms, and basic system‑design concepts
- Coursework or projects demonstrating machine‑learning fundamentals (regression, classification, DL models, Agentic AI)
- Familiarity with SQL and eagerness to dive into data pipelines (Kafka, MongoDB, BigQuery, or similar)
- Ability to be self‑directed and learn quickly, with a strong desire to stay on top of the latest AI developments
- Comfort using AI tools—Cursor, GPT, Claude—to accelerate development
- Strong written and verbal communication skills; collaborative mindset
