We are a team of builders, dreamers, and data geeks. We don't just use AI as a buzzword; it is the core engine of our product.
The Role We are looking for an AI/ML Engineer who cares about code quality as much as model accuracy. You won't just be tweaking hyperparameters; you will own the full lifecycle of ML developmentfrom raw data to real-time inference in production.
If you love solving hard problems and want to see your algorithms impact thousands of users daily, this is the seat for you.
What You'll Build (Responsibilities)
- Design & Develop: Build and fine-tune state-of-the-art models for [specific use case, e.g., NLP, fraud detection, image recognition].
- Productionize: Work with the DevOps team to containerize and deploy models using Docker/Kubernetes.
- LLM Integration: Experiment with Large Language Models (LLMs), RAG pipelines, and prompt engineering to drive our new GenAI initiatives.
- Data Pipelines: Collaborate with Data Engineers to build robust training pipelines and feature stores.
- Monitor: implement MLOps tools to track model drift and performance in the wild.
What You Bring (Requirements)
- Experience: 3+ years of hands-on experience in Machine Learning or Data Science.
- Tech Stack: Expert proficiency in Python. Strong grasp of PyTorch or TensorFlow.
- Foundations: Solid understanding of math/stats (Linear Algebra, Probability, Optimization algorithms).
- Engineering: Experience with APIs (FastAPI/Flask) and cloud platforms (AWS/GCP/Azure).
- Bonus Points: Experience with vector databases (Pinecone, Milvus) or Hugging Face transformers.
Click the Easy Apply button or send your resume and a link to your GitHub/Portfolio to [Confidential Information]
