AI Engineer - California, United States

Role overview Build and operate AI systems for financial research and market intelligence, working with engineering, data science, quantitative research, product, and software teams. The work ranges from LLM-based research tools and retrieval pipelines to the services and infrastructure needed to run them reliably in production. The role focuses on technology and research workflows rather than investment advice or trade execution.

Responsibilities - Develop scalable machine learning applications, LLM research tools, retrieval-augmented generation pipelines, agents, and orchestrated workflows. - Build and optimize inference services, APIs, model integrations, and backend infrastructure. - Work with financial datasets, research documents, and market intelligence; implement embeddings, vector search, and document understanding. - Create evaluation, benchmarking, monitoring, and reliability practices for models and applications. - Improve performance, latency, scalability, security, and infrastructure efficiency; address risks such as hallucinations, prompt injection, and data leakage. - Collaborate on architecture, testing, planning, and production releases, with business travel exceeding 25% of annual working time.

Requirements - At least four years of professional experience in AI engineering, machine learning, or software engineering. - Strong Python and production software development skills; hands-on experience with PyTorch, TensorFlow, or a comparable framework. - Experience building with LLMs, RAG, embeddings, and AI APIs; understanding of evaluation, prompt engineering, and system reliability. - Experience with cloud infrastructure, Docker, CI/CD, API development, SQL, data pipelines, or scalable backend systems. - Strong analytical and debugging skills, professional English fluency, and a relevant degree in computer science, AI, machine learning, or a related field. - Able to work remotely from California, travel more than 25% annually, and legally work in the United States.

Nice to have - Background in fintech, financial services, quantitative research, or market intelligence. - Experience with agentic AI, tool calling, workflow orchestration, multimodal models, vector databases, Kubernetes, MLOps, or distributed systems. - Experience building secure enterprise AI applications or working with financial market data and time-series analysis.

Benefits and work setup - Full-time remote work within California; annual base salary of $125,000–$155,000. - Opportunities to shape AI architecture, reliability, and engineering standards while collaborating with international teams. - Business travel may include meetings, workshops, conferences, and cross-team planning; approved travel expenses are covered under policy.