AI Jobs in Palo Alto

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Translate business requirements into requirements for AI/ML models; prepare data to train and evaluate AI/ML/DL models; build AI/ML/DL models by applying state-of-the-art algorithms, especially transformers; leverage existing algorithms from academic or industrial research when applicable; test, evaluate, and benchmark the AI/ML/DL models, and publish the models, data sets, and evaluations; deploy models in production by containerizing the models; work with customers and internal employees to refine the quality of the models; establish continuous learning pipelines for models with online learning or transfer learning; build and deploy containerized applications on cloud or on-premise environments.

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Contributors design original computational statistics problems that simulate real mathematical research workflows, creating problems requiring Python programming to solve using libraries like Numpy, SciPy, and Sympy. They ensure problems are computationally intensive and require non-trivial reasoning chains in areas such as number theory, combinatorics, graph theory, and numerical analysis. The problems are based on real research challenges or practical mathematical applications. Contributors verify solutions using Python with standard mathematical libraries and document problem statements clearly with verified correct answers.

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Contributors may generate prompts that challenge AI, evaluate AI-generated solutions for correctness, assumptions, and logic, improve AI reasoning to align with first principles and accepted standards, and apply structured scoring criteria to assess multi-step problem solving.

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Contributors may generate prompts that challenge AI; evaluate AI-generated solutions for correctness, assumptions, and logic; improve AI reasoning to align with first principles and accepted standards; and apply structured scoring criteria to assess multi-step problem solving.

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Design original computational statistics problems that simulate real mathematical research workflows; create problems requiring Python programming to solve using libraries such as Numpy, SciPy, and Sympy; ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes; develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis; base problems on real research challenges or practical applications from mathematical practice; verify solutions using Python with standard mathematical libraries; document problem statements clearly and provide verified correct answers.

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As a Senior Staff AI Engineer at Hippocratic AI, you will define the multi-year technical strategy and architectural roadmap for the AI platform encompassing RAG, multi-agent systems, real-time voice, evaluation, and safety, aligning leadership, engineering, and research around it. You will architect foundational platforms and systems used across multiple products, teams, and partners, making critical technical decisions for the company's future. You will partner directly with executive, product, and clinical leadership to translate long-term healthcare goals into technical initiatives. Additionally, you will represent engineering in board-level, partner, and regulatory discussions, identifying and driving both zero-to-one and one-to-n innovations that expand the company's capabilities. You will own the company-wide safety and evaluation standards, setting gates and measurement systems that all agents, partner deployments, and model changes must pass. Furthermore, you will mentor Staff and Senior engineers, influence hiring and leveling, multiplying the impact of engineering teams, and represent Hippocratic AI externally at conferences, through publications, and partner engagements in the healthcare AI community.

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As a Staff AI Engineer at Hippocratic AI, you will set the technical direction for voice-based generative AI in healthcare, architect intelligent systems powering clinically safe healthcare agents, and own one or more core AI domains end-to-end including RAG, agent orchestration, evaluation, or real-time voice. Responsibilities include designing foundational production-grade AI pipelines for voice-based generative healthcare agents incorporating multi-step reasoning, agent orchestration, and evaluation systems; leading cross-functional initiatives with product, clinical, and engineering teams to translate healthcare workflows into safe and scalable AI experiences; representing engineering in clinical and partner conversations; driving innovation using state-of-the-art LLMs, retrieval systems, and streaming architectures; setting standards for AI-native workflows supporting real-time, conversational, and long-running interactions across healthcare contexts; owning safety and evaluation standards across model evaluation, safety testing, and observability; defining production gates for agents; mentoring senior and mid-level engineers; and elevating team quality through code and design reviews.

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Serve as the technical point of contact for healthcare customers, translating ambiguous problems into scalable solutions. Build and deploy AI systems, including RAG pipelines and multi-agent workflows, and develop real-time conversational AI systems. Work with healthcare data integration standards such as HL7 v2, FHIR, REST APIs, and X12, and build pipelines using Python and SQL. Own the full lifecycle of the AI solutions from design to monitoring, including troubleshooting production issues. Collaborate with product, AI research, and clinical teams. Operate onsite at customer locations in Minneapolis, MN, with occasional travel to Hippocratic AI headquarters for strategic planning and team sessions.

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Ship critical infrastructure by managing real-world logistics and financial data for the largest enterprise in the world. Own the why by building deep context through customer calls and understanding Loop’s value to customers, pushing back on requirements if a better, faster solution exists. Work across system boundaries with full-stack proficiency, including frontend UX, LLM agents, database schema, and event infrastructures. Leverage AI tools to automate boilerplate work, focusing on quality, architecture, and product taste. Constantly optimize development loops, refactor legacy patterns, automate workflows, and fix broken processes to raise the velocity bar.

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The Staff Software Engineer is responsible for owning the end-to-end technical vision for the EDR telemetry and detection workstream, rallying the team from concept through shipping, iterating, and deprecating. This includes producing production code contributions in a modern backend language such as Go, Rust, or Python within a service-oriented environment and setting technical standards through design reviews, code quality, and operational discipline by example. The role involves mentoring engineers, building frameworks and architecture to enable high performance, partnering with the hiring team on recruiting and leveling engineers, and holding the team accountable for outcomes by managing risks and tradeoffs early and in writing. The engineer translates ambiguous product goals into concrete technical roadmaps, makes decisions regarding build versus buy or integration with business context, partners closely with product management in PRD reviews and sprint planning, and sequences MVP development effectively. Domain expertise is required in EDR platforms including telemetry, API level, detection logic, alert triage, and SOC team workflows. The engineer builds ground truth datasets, manages false positive and false negative tradeoffs and confidence scoring, and owns the detection and measurement methodology, including ground truth methodology, confidence scoring, calibration, and defining what constitutes correct tuning recommendations. The position requires collaboration, and contributing both to leadership and hands-on coding, and may include up to 10% travel.