My Client is a fast-moving startup based in NYC building cutting-edge AI-powered solutions to solve real-world problems in the building industry. Our mission is to harness the latest advances in large language models (LLMs) to build intuitive, human-centric tools. We believe small teams can make a big impact—and we’re looking for people who thrive in dynamic, high-ownership environments.
Role Overview
We’re seeking a Machine Learning Engineer with a strong focus on prompt engineering to help us develop, fine-tune, and deploy LLM-driven applications. You’ll work closely with our product, engineering, and design teams to iterate quickly on new features, prototypes, and research-backed implementations that bring language models to life in production.
What You’ll Do
- Design, test, and optimize prompts for large language models (e.g., GPT-4, Claude, Gemini) across a range of tasks.
- Fine-tune open-source or proprietary language models using instruction tuning, RLHF, or LoRA-based approaches.
- Develop robust evaluation pipelines to assess model performance, safety, and reliability.
- Collaborate with product and UX teams to integrate LLM functionality into real-world user flows.
- Research and experiment with new prompting techniques (e.g., chain-of-thought, self-reflection, retrieval-augmented generation).
- Write reusable components and tools to streamline LLM integration and testing.
- Monitor model behavior in production and iterate on prompts/models based on user feedback and performance data.
What We’re Looking For
- 2–5+ years of experience in machine learning, NLP, or applied AI.
- Experience working with large language models (OpenAI, Anthropic, Hugging Face, Cohere, etc.).
- Strong Python skills and familiarity with ML frameworks like PyTorch or TensorFlow.
- Deep understanding of prompt engineering techniques and LLM behavior.
- Experience with tools for LLMOps (e.g., LangChain, Weights & Biases, MLflow, etc.) is a plus.
- Ability to balance research exploration with practical product needs.
- Excellent communication skills and a collaborative, startup-minded attitude.
Nice to Have
- Experience with vector databases (e.g., Pinecone, Weaviate, FAISS).
- Familiarity with API-based LLM deployments and serverless infrastructure.
- Published research or blog posts in the NLP/LLM space.
- Previous startup experience or working on small, agile teams.
What We Offer
- Competitive salary and early-stage equity
- Flexible hybrid schedule with a beautiful workspace in NYC
- Opportunity to work on cutting-edge AI applications with real user impact
- A small, ambitious, and collaborative team
- Generous vacation, healthcare, and wellness benefits
