About the role
You'll architect, deploy, and monitor production AI/ML and GenAI services that directly power the CheQ experience for millions of users. This isn't a research sandbox; you'll integrate LLMs and GenAI models (GCP-first) into live systems, work closely with product and engineering, and help shape the technical roadmap for your domain.
Responsibilities:
- Full-stack ownership architecture through deployment through monitoring; no hand-offs.
- Work directly on consumer-facing AI at fintech scale: real users, real money, real impact.
- Fast-moving startup environment: ship fast and see impact fast.
- Cross-functional exposure: you'll shape roadmap decisions, not just execute tickets.
Requirements:
- 5+ years in ML engineering, with 2+ years dedicated to AI/ML/LLM engineering.
- Strong Python, Pandas, NumPy, Scikit-learn, and LangChain/LlamaIndex.
- Hands-on with PyTorch/TensorFlow/Keras.
- Backend chops: FastAPI, Django, or Flask.
- Comfort across MySQL, MongoDB, Redis, and BigQuery.
- CI/CD experience (GitHub Actions) and event-driven systems (Kafka/RabbitMQ).
- Deep knowledge of LLMs, vector databases, prompt/context engineering, embeddings, and KV caching.
- GCP or AWS experience.