About the role
Responsibilities:
- Design, build, and deploy machine learning and AI models that power Transient. AI's core products (research automation, document intelligence, investor matching, and workflow orchestration).
- Work on applied NLP/LLM systems, including retrieval-augmented generation, structured extraction from unstructured financial documents, and model evaluation pipelines.
- Partner closely with product and founding engineers to translate capital markets workflows into scalable AI systems.
- Own model performance, reliability, and cost from experimentation through production deployment.
- Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration.
- Ensure systems meet the compliance, auditability, and security standards required in regulated financial environments.
- Collaborate with a distributed team across New York, Miami, Singapore, and India.
Requirements:
- 5+ years of experience building and deploying machine learning or AI systems in production.
- Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, or equivalent).
- Experience with LLM fine-tuning, prompt engineering, RAG architectures, or agentic systems is highly valued.
- Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring, versioning).
- Prior experience at a strong product company, high-growth startup, or a top-tier engineering background (IIT or equivalent) is preferred.
- Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity.
- Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory.