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.
Job Description
This role requires a strong 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 significant for success in this role.
Who we are looking for:
Python Experience: 5+ years of experience with Python.
Generative AI Experience: You must have experience with 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.
Test-Driven Development: Belief in and adherence to Test-Driven Development practices is essential. This means writing tests before writing code to ensure the quality and correctness of your work.
Responsibilities:
Design and Develop Scalable Machine Learning Systems: You will be responsible for collaborating with the tech team to design and build machine learning systems that are scalable and ready for production use from the start. This involves the end-to-end development of machine lea