Machine Learning Engineer



Posted on Jun 6, 2024

🔮 Machine Learning Engineer at Tune AI

We're looking for a Machine Learning Engineer at Tune AI.

At Tune AI, we're building the generative AI stack for enterprises and developers powered by open source models. Our vision is to become the AI infrastructure of the internet, and those who power the world. We're backed by Accel, Flipkart, Together Fund, Speciale Invest, Techstars, and other top-tier VCs.

As part of our work life, we work in office 5 days of the week from 11am to 7pm. We also have frequent team outings to bring everyone a little closer. Our pantry remains stocked up with your favourite snacks and we have an automated coffee machine that makes you brilliant cappuccinos as well as espresso shots when you need the jolt. Our office has dedicated in-house staff that can whip up food instantly for you so you can focus on what you do best. The best part? The beach is 500 meters away from our office so meetings at dusk can happen with sand between your toes.


  • Work with the platform team to create optimized ML pipelines, specialized for large-language models

  • Conduct research into fine-tuning and optimizing inference of large language models

  • Build pipelines to ingest and process data for training and fine-tuning models

  • Evaluate state-of-the-art large language models and compare their performance

  • Deploy trained models to the cloud and optimize strategies for serving them at scale


  • 4-6 years of experience in machine learning, data science, or MLOps

  • Strong understanding of large-language models and Retrieval Augmented Generation (RAG)

  • Proficient in Python, FastAPI, SQLAlchemy, Docker, PyTorch, Transformers, and GitHub

  • Good to have: Go, Kubernetes, Cloud (GCP, AWS, Azure)

  • Fluent with Linux


  • Experience working with machine learning in production environments

  • Knowledge of how large language model APIs work

  • Hands-on experience with fine-tuning large language models

  • Self-sufficient and active in large language model communities (e.g. r/localLLaMA)