Hybrid
Full Time
should be looking for:
- 5+ years of experience as a data scientist / AI Engineer, ideally in customer-facing, production-deployed projects.
- Solid understanding of deep learning concepts, supervised / unsupervised / self-supervised / reinforcement learning.
- Solid understanding of Large Language Models, Transformers architecture, self-attention, mixture of experts, and embedding models.
- Proven experience with advanced Retrieval Augmented Generation, vector DBs, graph DBs and prompt engineering.
- Expertise with AI agents design, orchestration and optimisation.
- Experience with LangChain & LangGraph (preferred) or CrewAI / LlamaIndex
- Experience with model fine-tuning.
- Hands-on data pre-processing experience.
- Strong Python expertise.
- Proficiency in ML frameworks such as PyTorch, TensorFlow, or similar.
- Experience with AWS development and deployment (ECS, Lambda, S3).
- Experience with AWS AI/ML/GenAI platforms: AWS SageMaker & AWS Bedrock.
- LLMOps expertise (LangFuse (preferred) or similar, e.g. LangSmith).
- Familiarity with Docker and Kubernetes.
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