Remote AI Engineer Intern: Build Production-Grade AI

Gravity

United States

Remote

USD 150,000 - 230,000

Full time

10 days ago

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Job summary

Gravity is seeking an AI/ML engineer to join a remote-first engineering team based in India, focused on shipping production-grade AI solutions.

You will integrate large language models using frameworks like LangChain, build agentic systems that plan, reason, and use tools, and design recommendation engines with solid MLOps and CI/CD foundations.

Open, collaborative, and results-driven, you’ll own features end-to-end in a fast-moving startup environment.

Qualifications

  • Proven track record shipping AI projects.
  • Proficiency in Python and fast development pace.
  • Knowledge of LLM frameworks and agentic architectures.
  • Experience with recommendation systems.
  • Understanding of MLOps and deployment pipelines.
  • Ability to work independently while collaborating with others.
  • Thrives in a remote-first startup environment.
  • Writes maintainable, production-ready code.

Responsibilities

  • Integrate large language models into applications using frameworks like LangChain.
  • Build agentic AI systems that plan, use tools, and reason through multi-step problems.
  • Design and implement recommendation engines.
  • Set up MLOps infrastructure and CI/CD pipelines to support continuous deployment.
  • Take projects from concept through production with minimal supervision.
  • Write code you can stand behind with focus on quality and maintainability.

Skills

Python
LangChain
LLM frameworks
MLOps
CI/CD
Independent problem-solver
Collaboration

Job description

Gravity is seeking an AI/ML engineer to join a remote-first engineering team based in India, focused on shipping production-grade AI solutions.

You will integrate large language models using frameworks like LangChain, build agentic systems that plan, reason, and use tools, and design recommendation engines with solid MLOps and CI/CD foundations.

Open, collaborative, and results-driven, you’ll own features end-to-end in a fast-moving startup environment.

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