Job Description

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.

Your Responsibilities:

+ 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 LangChain or LlamaIndex, 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 AutoGen, 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.

What we look for:

+ 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 AutoGen, CrewAI, or LangGraph-like toolkits.
- Experience with distributed training, model optimization, quantization, or GPU acceleration.
- Knowledge of DevOps/MLOps tooling for deploying LLM-based systems.
- Contributions to open-source LLM or RAG projects.

What we offer:

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.