Python AI Jobs

View detail

Contributors design original computational statistics problems simulating real mathematical research workflows, create problems requiring Python programming solutions using libraries such as Numpy, SciPy, and Sympy, ensure problems are computationally intensive and not solvable manually within reasonable timeframes, develop problems needing non-trivial reasoning in areas like number theory, combinatorics, graph theory, and numerical analysis, base problems on real research challenges or practical applications, verify solutions with Python and standard mathematical libraries, and document problem statements clearly with verified correct answers.

View detail

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 (days/weeks); 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; and document problem statements clearly and provide verified correct answers.

View detail

Contributors design original computational statistics problems simulating 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 in reasonable timeframes; develop problems involving non-trivial reasoning chains in areas including number theory, combinatorics, graph theory, and numerical analysis; base problems on real research challenges or practical applications; verify solutions with Python using standard mathematical libraries; and document problem statements clearly with verified correct answers.

View detail

Contributors may 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, and document problem statements clearly while providing verified correct answers.

View detail

Design original computational statistics problems that simulate real mathematical research workflows; create problems requiring Python programming to solve using Numpy, SciPy, Sympy; ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes; develop problems requiring non-trivial reasoning 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.

View detail

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.

View detail

Contributors design original computational statistics problems simulating real mathematical research workflows, create problems requiring Python programming (using Numpy, SciPy, 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, and document problem statements clearly with verified correct answers.

View detail

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.

View detail

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.

View detail

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.