My client is a Series C scale-up (raised $70m in 2025) building the commerce OS used by household names. They’re hiring a Senior Data Scientist to take point on agentic AI: architect multi-agent workflows, fine-tune LLMs, and own the metrics that prove business impact.
Their platform already powers 3,000+ brands and automates complex operations at scale.
Why join?
* Own the blueprint – step into a live but early agentic stack and set the standards for architecture, governance and evaluation.
* Real product leverage – your orchestration, models and metrics will drive outcomes for thousands of daily decisions across 1,000+ brands.
* LLMs in production – design conversational flows, fine-tune models and stand up success frameworks for agent systems
* Remote-first culture
The role
* Agentic design & orchestration: Define agent roles, tool use, memory and hand-offs; build resilient multi-agent journeys for discovery → advice → purchase.
* LLM training & tuning: Run LoRA/QLoRA/full fine-tunes with PyTorch/Hugging Face on Vertex AI; own data curation and the evaluation harness.
* Measurement: Set and track KPIs (task completion, hand-off success, latency/cost/factuality, business outcomes).
* Classical ML where it counts: Ship intent classifiers, outcome forecasters and recommendation pipelines with scikit-learn/XGBoost/LightGBM.
Stack (core)
* Python (production-grade)
* LLM tooling: PyTorch, Hugging Face, TensorFlow
* Fine-tuning: LoRA / QLoRA / full training
* GCP / Vertex AI: Training, Pipelines, Registry/Deploy
* Experimentation: SQL, A/B test design, causal thinking
* Predictive: scikit-learn, XGBoost, LightGBM, Google AutoML