AI/ML Engineer

Build production AI systems — not demos. You'll design and ship RAG pipelines, LLM integrations, and ML-powered features as part of client engagements across fintech, healthcare, and SaaS.

About the role

This role sits at the intersection of ML engineering and software engineering. You'll be building production AI systems — RAG pipelines, fine-tuned models, embedding systems, and LLM-powered features — that real users rely on every day.

You'll work directly with clients to scope AI features, design evaluation frameworks, and iterate on model performance in production.

What you'll do

• Design and implement RAG pipelines with hybrid retrieval and reranking
• Integrate LLM APIs (OpenAI, Anthropic) into production applications
• Build evaluation harnesses and golden-set testing for AI features
• Fine-tune and deploy open-source models (Hugging Face, Ollama)
• Design data pipelines for feature engineering and model training
• Collaborate with engineering teams to integrate ML features into existing systems

Requirements

• 3+ years of ML engineering or applied AI experience
• Production experience with LLM APIs and prompt engineering
• Strong Python skills and familiarity with ML frameworks (PyTorch, scikit-learn)
• Experience with vector databases (pgvector, Pinecone, Chroma)
• Understanding of RAG architectures and their failure modes
• Ability to communicate technical ML concepts clearly to non-technical stakeholders

Nice to have

• Experience fine-tuning or RLHF on open-source models
• Background in NLP or information retrieval
• Experience with streaming architectures for real-time ML inference
• Published research or technical writing