AI/ML Engineer

📋 Description

• Build production AI systems: API to training to inference.
• Train and deploy our DSLM: Fine-tune models, production infra.
• Integrate ML into backend: extend FastAPI, PydanticAI, FastMCP, Memgraph.
• Own inference performance: Hit sub-200ms latency.
• Shape Project Genome foundation: Ingest/process data for learning.
• Mentor through code reviews and pairing.
• Work across AI stack: FastAPI, training pipelines, deployments.

🎯 Requirements

• Must have: 5+ years building production Python systems.
• Must have: Strong software engineering fundamentals.
• Must have: Experience integrating LLMs in apps.
• Must have: Understanding ML training workflows.
• Must have: Docker, CI/CD, production deployment.
• Must have: Can read PyTorch code.
• Nice to have: Fine-tuning experience (LoRA, QLoRA).
• Nice to have: Graph databases (Memgraph, Neo4j).