Vila Andrade, São Paulo
Senior Machine Learning Engineer
Our client is a stealth mode startup building a next-gen enterprise AI platform that automates repetitive tasks for everyday business users. Most current solutions also require heavy services and implementation to be successful, making them inaccessible to smaller organizations and non-technical users. Our client is building the first self-service AI automation platform for everyday business users.
They are backed by top-tier VCs. The founders are a strong team coming from leadership positions at Google and UiPath. They are creating a future in which everyone can use AI to save time and achieve their full potential.
An ML lead to take ownership of building a scalable “auto ML” platform from scratch.
– Take full ownership of a scalable “auto ML” platform
– Influence the overall product and engineering strategy
– Brainstorm, innovate and prototype cutting edge ML models and infrastructure
Led the development of all aspects of the Machine Learning (ML) process, including data collection and labeling, building training and validation pipelines, data analysis, and everything else required to develop and launch models into production.
Led the design and implementation of auto ML pipelines for various ML tasks, including classification, regression, clustering, recommendation and search.
Drive experiments and iterate on refining and improve ML models
Collaborate with product engineers to develop and integrate ML models.
Ensure models and the overall inference pipelines run efficiently on Cloud and/or browser
Adopt standard machine learning methods to best exploit modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU)
Rock solid algorithm, data structure and coding skills
Experiences with end to end ML application development, including data engineering, model tuning, model serving and model serving
Experiences with NLP models development
Experiences with developing and debugging in Python, C/C++ or equivalent programming languages
Experiences with giant language model development
Experiences with neural network architecture search
Exposure to architectural patterns of large scale software applications
Python, Tensorflow, Pytorch, NLP, distributed systems, ray (optional), GCP (optional)