Data Scientist Tier Entrepreneurs

A Message from Our CEO:

We are seeking a highly skilled Data Scientist with deep expertise in modern AI/ML systems, including LLMs, multimodal models, fine-tuning techniques, and advanced retrieval architectures. In this role, you will design, prototype, and deploy AI-powered solutions that leverage state-of-the-art language, vision, and agentic frameworks. You will work closely with engineering, product, and research teams across the US and Europe to bring cutting-edge AI capabilities into production environments.

• Design, build, and optimize LLM-powered systems using OpenAI, Anthropic, and open-source/local model families.
• Architect and implement RAG pipelines, including hybrid search, query rewriting, prompt optimization, and reranking strategies.
• Develop and maintain vector database infrastructures (Pinecone, Weaviate, Qdrant) for large-scale embedding storage and fast retrieval.
• Train, evaluate, and retrain embedding models for domain-specific semantic search and knowledge retrieval.
• Build and integrate multimodal AI solutions using OCR, CLIP, and modern vision architectures for text-image understanding.
• Apply fine-tuning techniques (LoRA/QLoRA) to adapt foundation models to organizational datasets and specialized tasks.
• Develop production‑ready AI applications using Python, PyTorch, and modern orchestration frameworks.
• Implement LLM orchestration with Lang Chain or Llama Index, including evaluators, tool abstractions, memory, and RAG components.
• Establish robust evaluation frameworks to measure model performance, reduce hallucination, and ensure reliability in production.
• Build agentic workflows using Auto Gen, CrewAI, or similar frameworks to power automation and multi‑agent collaboration systems.
• Stay current with research trends and apply theoretical and practical insights in Generative AI to drive innovation across the organization.

• Experience in applied machine learning or data science, with at least 2 years focused specifically on LLMs or Generative AI.
• Demonstrated experience building end‑to‑end RAG, fine‑tuning, or multimodal AI systems.
• Strong proficiency in Python, PyTorch, and AI tooling ecosystems.
• Experience deploying models at scale in production environments.
• Strong understanding of evaluation metrics, model reliability, and safety/reduction of hallucination.
• Familiarity with vector embeddings, vector databases, and semantic search.
• Experience with agent frameworks such as Auto Gen, CrewAI, or Lang Graph‑like toolkits.
• Experience with distributed training, model optimization, quantization, or GPU acceleration.
• Knowledge of Dev Ops/MLOps tooling for deploying LLM‑based systems.
• Contributions to open‑source LLM or RAG projects.

• Competitive salary and performance‑based bonuses.
• Fully remote, flexible work environment.
• Modern laptop and hardware provided by us.
• Specialized training in AI, automation, and digital productivity tools.
• Global exposure—collaborate with top‑tier founders and fast‑growing startups.
• Continuous learning and career growth opportunities in an international environment.