About the Role

You will build and ship core parts of Fearn’s platform from deploying our custom models to optimizing for faster inference time. You'll play a crucial role in architecting and building robust AI systems for language, images, and multimodal inputs.

Key Skills

  • Proficiency in Python and familiarity with ML frameworks (PyTorch, Transformers, etc.)

  • Deploy and manage ML inference endpoints using open-source tools like vLLM, TGI, or similar serving frameworks

  • Optimize model performance for latency, throughput, and cost on GCP infrastructure

  • Collaborate with research and product teams to bring new models from prototype to production

  • Thrive in small, fast-moving teams where speed and autonomy matter

Bonus

  • Experience with open source models

  • Experience with GPU infrastructure and optimization techniques

  • Strong GCP experience, especially with Compute Engine, GKE, Vertex AI, or Cloud Run

  • Experience with quantization, batching strategies, or multi-model serving

About our interview process

We run an efficient and thorough interview process to ensure a good fit on both sides. That being said, we will try our best to make the process as fast as you need it to be. Please see details below:

  • Member of technical staff

    1. 15 min introductory chat: We will tell you a bit about Fearn, learn about you and your prior experiences, and answer any questions you might have. The goal is to assess whether or not we are aligned.

    2. 30 min technical interview: We will share a technical coding problem during a live session. We will work together on your solution to understand your thought process. Our goal is to understand your problem solving skills and how you structure your approach.

      1. Prep: We will ask that you share your entire screen, close all unrelated apps, and close all tabs aside from the Google Meet and Docs tabs.

    3. Reference checks: We will conduct a minimum of 2 reference checks. Be prepared to share references of prior employers, classmates, or anyone you might have worked with in the past.

    4. Onsite: Join us in person to meet the rest of the team!

    5. Decision!

We may use AI note takers during interviews to make sure we are fully focused on you. Please speak to your interviewer if this is an issue for you.