Bachelor's degree in Computer Science or a related field
2+ years of AI/ML engineering experience
Hands-on experience building GenAI solutions, prompt engineering, fine-tuning and serving LLMs, search and embeddings, using common frameworks (LangChain/LangGraph, LlamaIndex)
Understanding of statistical, ML and deep learning algorithms
Working knowledge of cloud ML services, preferably AWS (Bedrock, AgentCore, SageMaker)
Proficiency in Python and core ML libraries and frameworks (scikit-learn, PyTorch, HuggingFace, TensorFlow, Transformers)
Familiarity with containerization and orchestration tools
A collaborative mindset, with openness to feedback and eagerness to grow your craft
Willingness to support and learn from more senior teammates on the ML crew
Autonomy, adaptability and a consistently positive presence on the teams you work with
Building and deploying agents with common patterns (Agentic RAG, NLQ) and frameworks (smolagents, strands-agents)
MLOps/LLMOps experience, preferably in AWS, along with standard tooling (MLFlow, LangFuse)
Experience in consultancy environments or startups, including working directly with clients, managing projects and adapting to different settings
Excellent English, as a global team, we work entirely in English for meetings, customer calls and business communications
CV written in English
Curious: You strive to learn and grow into different industries with a modern tech stack
Autonomous and positive: You excel in a fully remote, globally distributed team
Team player: You enjoy a collaborative approach
Adaptable: You operate with a startup mindset and move at a startup pace
Coachable: You take feedback well and are eager to grow your skills