Data Science Team Leader

Requirements:
M.Sc. or higher in Computer Science, Mathematics, Engineering, or a related quantitative field.
7+ years of hands-on experience building and deploying ML/AI solutions in production, including 2+ years leading or growing a data science/ML team.
Proven experience designing and shipping GenAI-based product features and multi-agent systems using modern orchestration frameworks such as LangGraph, CrewAI, or AutoGen, including RAG, vector databases, and tool/function calling.
Practical experience with the agentic production stack: observability/eval tooling (e.g., Langfuse), durable workflow orchestration, and typed service design.
Strong foundation in classical machine learning - supervised/unsupervised methods, feature engineering, model evaluation - and sound judgment for when to use classical models over LLMs.
Advantage: Demonstrated experience fine-tuning and deploying small/large language models, including SFT and preference/RL-based methods such as GRPO or DPO.
Advantage: Experience with model optimization and efficient serving: quantization, pruning, LoRA/QLoRA, and high-throughput inference frameworks such as vLLM.
Advantage: Experience designing end-to-end ML pipelines (versioning, training/tuning, deployment, testing, monitoring) on cloud-native infrastructure (Kubernetes, GCP/AWS).