AI/ML Engineer

WTMF

To pull this off, we need people who live and breathe AI/ML. People who look at a messy dataset and see… potential. People who get excited about fine-tuning models the way others get excited about cricket scores or Netflix drops.

Someone who:

• Thinks transformers are cooler than Optimus Prime.
• Knows that “loss” isn’t just an emotion, it’s something you reduce.
• Gets a little too happy when an experiment finally converges.
• Wants to work on AI that feels less robotic and more human.

• Train, fine-tune, and optimize models that power our AI companion.
• Experiment with LLMs, embeddings, and recommendation systems to make conversations smarter and more personal.
• Work with data (structured, unstructured, and occasionally chaotic) to give our bestie a memory.
• Collaborate with product and design teams to translate “wouldn’t it be cool if…” into working features.
• Keep an eye on performance, cost, and ethics — because great AI should also be responsible.

• A solid background in ML, deep learning, or NLP (bonus if you’ve wrestled with large language models before).
• Comfort with frameworks like PyTorch or TensorFlow.
• Enough math/statistics chops to know why your model is misbehaving.
• The ability to prototype quickly, fail gracefully, and try again.
• Experience in productionizing models is a big plus — research is great, but shipping is magic.

• You’ll be shaping the brain of an AI bestie used across the globe.
• You’ll have freedom to experiment, iterate, and see your work impact users directly.
• Competitive pay, equity options, and the chance to be part of a small but ambitious team.
• Work from anywhere, with people who are equally obsessed with AI and making it useful (and fun).