Job Details

At Synagi, we are pushing the frontier of distributed and decentralised AI agents. Our research spans vector-driven retrieval systems, agentic swarms, and resource-efficient multi-agent architectures—all with a sharp focus on real-world performance and human-in-the-loop alignment. We explore scalable, context-aware multi-agent designs that outperform monolithic approaches and keep compute costs in check.

Role

You will own the AI layer that powers Synagi's agents—from vector databases and retrieval-augmented generation (RAG) pipelines to fine-tuning compact transformer models and classic ML solutions where they make sense. Your work will turn raw data into fast, reliable intelligence that scales with our product ambitions.

Core Responsibilities

• Vector databases – Design schemas, sharding strategies, and ANN indexes (Milvus, Vespa, or pgvector) to store and query billions of embeddings.
• RAG pipelines – Build and maintain end-to-end retrieval workflows: query rewriting, hybrid BM25 + vector search, and re-ranking for fact-grounded answers.
• Model creation & fine-tuning – Train or adapt lightweight transformer models using techniques such as LoRA; develop classic ML models when they outperform deep nets.
• MLOps – Containerise AI workloads with Docker, deploy and scale them on Kubernetes, and automate training/evaluation workflows.

Must-Have Qualifications

• 3+ years of production machine learning experience in Python; shipped at least one transformer-based model.
• Proficient with PyTorch or JAX for custom model development and fine-tuning.
• Practical experience with vector databases and RAG techniques.
• Comfortable with CUDA tooling for debugging and optimising GPU workloads.
• Able to design and train ML models from scratch for small-parameter or classical ML tasks.

Nice-to-Haves

• Experience with DeepSpeed or vLLM for efficient inference serving.
• Familiarity with LangChain or LlamaIndex for rapid agent prototyping.
• Interest in decentralised or edge deployments (e.g., WASM at the edge) for ultra-low-latency inference.

Applying

Send your resume—plus a short note (3–5 sentences) describing a production system you scaled or a performance bug you crushed—to ...@gmail.com .

We offer highly competitive salary, early-stage equity, and an opportunity to be the backbone of synergetic general intelligence.

Synagi is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.