AI & ML Ops Engineer Intern

About Chartmetric

Chartmetric, Inc. is a 9-year-old startup specializing in music data analytics. We are trusted by Universal Music Group, Sony, Warner, Facebook, and Apple Music, as well as hundreds of other music companies and industry professionals.We have created a self-service data dashboard for the music industry to better understand the activity happening around artists. We combine hundreds of thousands of real-time data points across iTunes, Spotify, Youtube, Google, Facebook, Twitter, and more through our beautifully designed tool in order to make sense of the increasingly complex landscape of the music industry.

About the role

Chartmetric is looking for a hands-on, infrastructure-savvy AI & ML Ops Engineer Intern to join us for a focused 3-month engagement. You’ll collaborate closely with our Product & Engineering Leaders to prototype and operationalize cutting-edge AI applications & infrastructure — focussed on LLMs, but with a forward-looking vision toward supporting fine-tuned, multi-modal generative models (text, image, audio, video).

This role is ideal for an engineer who’s deployed real-world open-source LLM models and/or ML systems and is eager to go beyond basic API integration. You should be comfortable setting up and fine-tuning models, standing up infrastructure, and shipping usable features—quickly and independently.

What you'll do

• Set up and optimize local model infrastructure (LLMs via Ollama, LangChain, vector DBs, etc.).
• Rapidly implement AI-powered features like Smart Search, API Assistants, and Internal tools.
• Fine-tune open-source models on domain-specific data for improved performance and control.
• Contribute to infrastructure that supports future in-house generative models (image, audio, video).
• Support efforts like Model Control Panel (MCP) and internal orchestration pipelines.
  

Qualifications

• Have shipped ML/AI systems—ideally with fine-tuning or deployment of LLMs or generative models.
• Understand vector search, embeddings, and model orchestration frameworks.
• Have light-to-moderate MLOps experience (model serving, logging, monitoring, reproducibility).
• Work well independently and execute quickly with minimal guidance.
• Are genuinely excited about pushing the boundaries of applied AI.

Bonus Points For

• Experience with prompt engineering and vector databases.
• Experience with other modalities: image, audio, or video generation.
• Familiarity with tools like Hugging Face, LoRA, Triton, Weaviate, or custom runners.
• Comfort managing GPU resources, Docker environments, or distributed inference loads.
• SQL and general database fluency—especially if you’ve connected AI tools to structured data.
  

We’re looking for a builder—someone who wants to own the full loop: from experimentation to deployment to iteration. If that’s you, let’s talk.