Mid-Level Python Backend Engineer for AI Research Systems

Wintermeyer Ventures

San Mateo (CA)

On-site

USD 200,000 - 250,000

Full time

3 days ago
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Job summary

Wintermeyer Ventures in San Mateo, California is seeking an engineer to join a small team building AI systems that can autonomously conduct research. You will develop the backend and infrastructure that support agentic discovery and advance automated scientific work.

You will write production-grade Python, build backend infra, and collaborate with researchers and engineers on agentic search and model post-training systems, while focusing on observability and performance for customer-integrated

Qualifications

  • Two or more years of software engineering experience, in the two to five year range.
  • Experience building production backend systems with advanced Python.
  • Background working with AI/ML infrastructure or backend systems.
  • Familiarity with Google Cloud Platform and agentic systems.
  • Strong production engineering skills and the ability to work collaboratively in a fast-moving environment.

Responsibilities

  • Build and maintain backend infrastructure for AI research systems.
  • Write production-quality Python code to improve system capabilities, reliability, and performance.
  • Collaborate with researchers and engineers on agentic search systems and model post-training infrastructure.
  • Contribute to machine learning infrastructure, observability, and performance optimization for customer-integrated systems.
  • Own engineering problems end to end, from design through deployment.

Skills

Python
Backend
AI/ML infrastructure
Google Cloud Platform
Agentic systems
Collaborative work

Job description

Wintermeyer Ventures in San Mateo, California is seeking an engineer to join a small team building AI systems that can autonomously conduct research. You will develop the backend and infrastructure that support agentic discovery and advance automated scientific work.

You will write production-grade Python, build backend infra, and collaborate with researchers and engineers on agentic search and model post-training systems, while focusing on observability and performance for customer-integrated

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