- About Simplismart
- A bit about our product - Simplismart is an MLOps platform with 3 major suites:
- Training suite: Assemble and train any model, including LLMs, vision, audio, tabular, and tree models.
- Deployment suite: Most companies fail to make models production-ready. Our proprietary model deployment suite is 6x faster than HuggingFace’s enterprise suite and 12x faster than replicate.ai. Users can easily deploy (auto-scale) models trained on Simplismart (more optimised), import any model from HuggingFace, or even a Pytorch/Tensorflow artefact: Tensorflow, Pytorch, ONNX, JAX.
- Observability suite: Monitor model health, including load, latency, uptime, data drift, and concept drift.
This is an excellent opportunity for individuals looking to be part of a 0→1→10 in the next 2 years who want to experience what it is to build a product/business from scratch and hopefully start their own venture someday. Not so much for individuals who prefer stability over growth
Job Description
This role requires a solid background in machine learning,
proficiency in relevant programming languages and tools, a willingness to embrace challenges, and a commitment to the best software development and testing practices. Additionally, familiarity with cloud platforms and a dedication to staying current with industry trends are essential for success in this role.
Who we are looking for:
Python Experience: 2-5 years of experience with Python.
Generative AI Experience: You must be proficient in LLMs like Llama and Mistral and other Generative AI models like Whisper and Stable Diffusion.
Cloud Experience: You should be familiar with cloud computing platforms, with a preference for expertise in AWS and knowledge of platforms like Google Cloud Platform (GCP) or Microsoft Azure.
Experience with Docker and Kubernetes: You should be proficient in Docker and Kubernetes.
Test-Driven Development: Belief in and adherence to Test-Driven Development practices is essential. This means writing