Posha builds cooking robots that live inside your kitchen and cook food for you completely autonomously. Posha robots use AI and Computer Vision to consistently and reliably cook the best food for our users 🥘

See it in action: https://bit.ly/howposhaworks

Posha is a fast-growing Series-A funded startup backed by Tier-1 VCs including Accel Partners, Waterbridge Ventures, amongst others.

🤔 What can I expect from this role?

We’re looking for a driven and curious Deep Learning Engineer to join our ML team. This is a core ML role with a strong emphasis on Deep Learning — you’ll work on building real-world systems involving computer vision, recommendation models, and, optionally, large language models (LLMs).

You don’t need to come in knowing everything — but you must have a strong grasp of deep learning fundamentals and a portfolio that demonstrates you’ve built or trained real models. If you're excited to get your hands dirty with real data, ambiguous edge cases (because there will be a ton of them), and rapid iteration cycles, this is the right place for you.

🔧What will my work responsibilities look like if I join Posha?

• Solve real-world perception problems using deep learning (e.g., regression, segmentation, classification, object detection)
• Train, evaluate, and productionise models that run across a wide variety of conditions and edge cases on edge devices.
• Contribute to entirely new ML features — from idea to dataset collection to building prototype to production.
• Iterate rapidly on datasets and models based on feedback from deployed systems
• If you're familiar with LLMs, you'll also have opportunities to work on fine-tuning LLMs on our use-cases, and retrieval-augmented generation (RAG) for chat-bots.

😍 What makes you a match for us?

• A recent graduate from IITs/NITs
• Solid in math and ML fundamentals — not just using pre-trained models or scikit-learn.
• Comfortable in an ambiguous, fast-paced, high-ownership startup setup
• Always curious, always building, and not afraid to experiment
• Strong fundamentals in Deep Learning — CNNs, RNNs, transformers, optimisation, generalisation, etc.
• Experience working with PyTorch to train and debug deep models.
• Comfortable with Python and ecosystem tools (NumPy, pandas, Scikit-Learn, OpenCV)
• Good grasp of training pipelines, evaluation metrics, and systematic experimentation
• Eagerness to pick up new domains (CV, NLP, speech) as needed

🧬 Bonus (Nice to Have)

• Experience working with LLMs.
• Hands-on with fine-tuning LLMs, or multi-modal models
• Experience dealing with real-world, noisy, or edge-case-heavy data
• Familiarity with tools like HuggingFace, Weights & Biases, AWS, MLFlow.

🏃‍♀️ Why Join Us

• You’ll own end-to-end ML problems — not just work on a small piece of the pipeline
• You'll deploy models on real robotic systems running in actual homes
• Fast iterations, real feedback loops.
• You'll grow super fast — both in depth and breadth — in a tightly-knit ML team
• It’s a startup — so if you're excited by speed, ownership, and real impact, you’ll fit right in

🚀 Working at Posha

• What users have to say about our Product
• Twitter love from users
• How does Posha cook
• Our Website
• Watch Our Journey 📹