> Markdown version of [/jobs/ext/4636682-lead-ai-scientist](https://www.wearedevelopers.com/jobs/ext/4636682-lead-ai-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead AI Scientist - **Company:** Harnham Inc. - **Location:** New York, NY, United States (Remote available) - **Experience:** Expert - **Salary:** $240,000 - $260,000 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Artificial Neural Networks, Computational Linguistics, Python (Programming Language), Machine Learning, Tensorflow, Cloud Platform System, Pytorch, Retrieval-Augmented Generation, Large Language Models, Deep Learning, Information Technology, HuggingFace, Recurrent Neural Networks - **Published:** November 8, 2026 - **Apply:** https://www.juju.com/job/28_25304_7b764aa6003252e617bd4a0ce118844f ## About the Role * 7+ years of machine learning and NLP / LLM modeling experience in applied research and production environments * PhD in Computer Science, Computational Linguistics, Statistics or similar highly preferred * Technical leadership experience required; direct people management a plus * Experience with LLMs, agentic AI or generative AI for customer-facing applications * Background in: deep learning or NLP preferred; experience building neural networks like CNNs, RNNs, LSTM, or similar * Cloud environments (provider-agnostic), AWS or GCP a plus * Python, PyTorch, TensorFlow, Hugging Face, BERT, RAG experience preferred * Publication and patent history a plus * Strong collaboration and communication skills, including experience working with non-technical stakeholders * Independent problem-solver with a proactive mindset ## Description This is a tech-lead, model building / development-focused role-ideal for someone with a strong foundation in applied AI research and a passion for making machine learning work in the real world. You'll own experiments, iterate on PoCs, and help define how ML models are built for in production environments.