What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Bachelor’s or master’s degree in computer science Engineering or related technical field or equivalent practical experience
- 3–7+ years shipping ML/AI in production
- Strong Python and fluent in PyTorch or TensorFlow
- Hands-on experience with LLMs including prompting fine-tuning RAG and evals
- Solid MLOps skills including CI/CD for models monitoring and cost optimization
- Experience deploying on GCP or AWS with GCP preferred
- Comfort with vector DBs embeddings and retrieval systems
- Startup-speed execution
Nice to have
- Fast learner
- High ownership
- Startup pace
- Hands-on builder
Day to day
- Own the end-to-end AI pipeline including ingestion processing inference and monitoring
- Harden and improve the production ML stack for fast reliable cost-efficient deployment at scale
- Deploy and scale LLM VLM and speech models in production on GCP while optimizing latency cost and reliability
- Build RAG pipelines prompting and evaluation frameworks and create tooling to speed experimentation and shipping