Coding & Software Engineering

Member of Technical Staff, AI/ML Engineering

Full-timeRemote1 opening$160 - $300/hour

About this role

Join our team as a Member of Technical Staff, AI/ML Engineering, and drive the development of cutting-edge AI systems. Work alongside talented engineers to design, implement, and optimize advanced LLM-based solutions, leveraging your expertise in quantitative fields to create impactful, scalable products.

Skills

PythonLLMsAWSLangChainFastAPI

Key responsibilities

  • Design, build, and deploy AI/ML solutions with a focus on large language models (LLMs) using Python and AWS infrastructure.
  • Architect scalable APIs and microservices utilizing FastAPI, ensuring robust, high-performance systems.
  • Integrate LangChain and advanced AI frameworks to deliver innovative model interaction capabilities.
  • Collaborate with cross-functional teams to translate complex mathematical, statistical, or physics-based problem statements into actionable engineering solutions.
  • Apply core math, statistics, or physics knowledge to improve model performance, interpretability, and reliability.
  • Maintain high standards of code quality, documentation, and peer reviews within a fast-paced core team.
  • Communicate technical concepts and project progress clearly through both written reports and verbal discussions.

Required skills & qualifications

  • Advanced degree or demonstrable expertise in math, quantitative sciences, statistics, or physics.
  • Expert proficiency in Python for AI/ML engineering.
  • Hands-on experience deploying, fine-tuning, and integrating LLMs.
  • Strong background in AWS services and cloud-native ML workflows.
  • Proven track record using LangChain for chaining LLMs and orchestrating multi-step reasoning.
  • Solid understanding of FastAPI for building scalable APIs.
  • Exceptional written and verbal communication skills; ability to articulate complex technical topics with clarity.

Preferred qualifications

  • Experience delivering AI/ML solutions in production environments at scale.
  • Publication record or open-source contributions in AI/ML, applied mathematics, or computational science.
  • Familiarity with advanced prompt engineering or AI safety best practices.
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