Machine Learning Engineer

6 days ago

Jodhpur, Rajasthan, India WTMF AI Full time

At WTMF, we're on a mission to build not just an AI app, but an AI bestie — someone you can journal with, share your moods, plan your days, or just talk to when you need it. To make that work, we need a Machine Learning Engineer who can turn ideas into working systems that scale.

This isn't about research that lives in a PDF. It's about taking models, making them efficient, and putting them in the hands of real people across the globe.

Who we're looking for

Someone who:

  • Knows their way around ML pipelines like others know their way around Google Maps.
  • Gets a thrill out of optimizing inference speed or reducing model size.
  • Can wrangle messy datasets without losing patience (or hair).
  • Thinks "deployment" is where the real fun begins.
What you'll actually do
  • Build and optimize ML pipelines that power our journaling, mood tracking, and conversational features.
  • Work with LLMs, embeddings, and classifiers to make WTMF smarter over time.
  • Turn messy, real-world data into structured insights our AI can learn from.
  • Collaborate with AI/ML researchers, backend engineers, and product designers to bring features from idea to production.
  • Keep an eye on performance, scalability, and cost so our models run fast, smooth, and responsibly.
What you should bring
  • Solid experience with ML frameworks (PyTorch, TensorFlow, or similar).
  • Comfort with building and deploying ML systems end-to-end.
  • Strong data engineering fundamentals (ETL, feature pipelines, distributed systems).
  • Good grasp of statistics and optimization (you know why the model overfit before anyone asks).
  • Bonus: hands-on work with cloud platforms (AWS/GCP/Azure) and MLOps tools.
Why you might love this
  • You'll be making ML work in the wild — powering an AI companion that users actually talk to every day.
  • You'll see your models improve real conversations, not just benchmarks.
  • Competitive pay, equity options, and the freedom to work remotely.
  • A small, ambitious team where your contributions shape the product directly.

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