AI Engineering Intern (+PPO)

Gravity; United States; Remote; USD 150,000 - 230,000; Full time

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

Batch: 2026/2027/2028.

About the role:

• Develop AI-powered solutions as part of a remote-first engineering team based in India
• Contribute to shipping real, production-grade systems in a fast-moving startup setting
• Work alongside engineers who value technical depth, personal accountability, and results-driven execution

What you'll work on:

• Integrating large language models into applications using frameworks like LangChain
• Building agentic AI systems that can plan, use tools, and reason through multi-step problems
• Designing and implementing recommendation engines
• Setting up MLOps infrastructure and CI/CD pipelines to support continuous deployment
• Taking projects from initial concept through to production launch with minimal supervision
• Writing code you can stand behind, with rigorous attention to quality and maintainability

What we're looking for:

• Solid hands-on experience building and shipping actual projects, not just coursework
• Deep comfort with Python and the ability to move quickly without overthinking
• Knowledge of how LLM frameworks and agentic architectures work in practice
• Familiarity with recommendation systems and their implementation
• Understanding of MLOps practices and deployment pipelines
• Drive to solve problems independently while knowing when to ask for help
• Strong collaborative instincts paired with genuine conviction in your ideas and a willingness to hear others out
• Ability to thrive in a startup pace where ownership and execution matter more than titles