Remote position (Only candidates located in Argentina or Uruguay will be considered) At Ryz Labs, we are looking for an experienced Machine Learning Infrastructure Engineer to join one of our client's teams. Their ML platform is a critical part of their operations, enabling them to train and test a wide range of ML models for various real-world tasks. It also allows them to analyze vast amounts of data from terabytes of sensor recordings we capture daily. As part of the ML Infra team, you'll help them build and enhance their platform. They work with technologies such as Apache Beam (Dataflow) for pipelines, Bazel for builds, BigQuery via dbt, MongoDB and GCS for storage, Kubernetes for service deployment, and Airflow for workflow management. Key ResponsibilitiesDevelop and maintain ML infrastructure, such as sensor data ETL pipelines, hard example data mining, continuous training pipelines, annotation platform, etc.Develop MLOps system for managing lifecycle of ML cloud training and inference as a service pipelines. Continuously improve ML model development, management and deployment processes.Work together with ML engineers, design metrics for ML tasks to mine sensor data of interest.Design and implement algorithms, such as collaborative filtering, active learning, etc., to rank/score annotation candidates.Work with annotation provider on setting up the annotation process, quality control and feedback loops.Make sensor data and its derivatives widely discoverable and accessible for Robotics Engineers across the entire company.QualificationsBS or MS in computer science with focus in data engineering and large scale ML systems3+ years of industry experience building, running and improving large-volume ML training and validation pipelines.Experience with building native cloud applicationsExperience with large scale data processing pipelines in production.Proficient in at least one of the following languages: C++, Python, or Go.Hands-on experience and good knowledge of Computer Vision and Deep Learning.Strong tendency to automate own and others' workflows.What makes you standoutExperience with data discovery and visualization tools like Voxel51, FacetsExperience with database systems like BigQuery, MongoDBExperience with Nvidia Jetson platform, e.g. CUDA, TensorRT, etc.Experience with Big Data products such as Apache Beam/Spark/Hadoop, GCP BigQuery, AWS Redshift.About RYZ Labs:RYZ Labs is a startup studio built in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together is the passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world. Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge technologies in cloud computing to create applications that are scalable and resilient. We aim to provide diverse product solutions for different industries, planning to build a large number of startups in the upcoming years. At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists. Our values and what to expect:Customer First Mentality - every decision we make should be made through the lens of the customer.Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated.Ownership - step up if you see an opportunity to help, even if not your core responsibility.Humility and Respect - be willing to learn, be vulnerable, and treat everyone that interacts with RYZ with respect.Frugality - being frugal and cost-conscious helps us do more with less.Deliver Impact - get things done in the most efficient way.Raise our Standards - always be looking to improve our processes, our team, our expectations. Status quo is not good enough and never should be.
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