Senior Site Reliability Engineer, Machine Learning Platform (Kubernetes)
Paris, France
Applications have closed
SoundHound Inc.
SoundHound’s advanced, independent voice AI platform is connecting people with brands through “Conversational intelligence that’s more human™SoundHound Inc. builds voice AI products that make it easier for people to engage with the world around them. We do this by creating custom voice assistants that make it possible for companies to extend their brand in new and meaningful ways. Today, our customized voice AI solutions allow people to talk to phones, cars, smart speakers, mobile apps, coffee machines, and every other part of the emerging ‘voice-first’ world.
To provide the fastest and most accurate voice assistants on the market, we leverage many deep learning models. As such, we have built a GPU-based Machine Learning platform to facilitate ML training and inference. We are looking for a motivated engineer with experience in distributed systems and Machine Learning workflows to expand and manage the ML platform.
As a member of our Language Modeling team, you have an opportunity to bring many state-of-the-art NLP models to production. We look forward to connecting with you if you’re drawn to this type of work.
In this role you will:
- Expand and manage the GPU-based Machine Learning platform
- Develop tools to scale ML training and inference
- Build tools and infrastructure that will benefit all ML teams
- Productionize ML models
We would love to hear from you if:
- You graduated with a Bachelor’s degree in Computer Science
- You have spent at least two years working with kubernetes
- You have experience building and managing distributed systems
- You are knowledgeable in GPU-based ML model training and inference
- You have experience with DevOps tools such as ansible or terraform
- You are comfortable working in a Unix environment and using the applicable tools
We’d be especially excited if you have scaled out an ML deployment or have experience with ML toolkits like kubeflow, TFX, or MLFlow. Also, be sure to let us know if you have scaled GPU-based ML training across multiple nodes.
Here at SoundHound, diversity, equity, and inclusion are key to who we are as a company. With a mission to build Voice AI for the world, creating a team with global perspectives is critical to our success.
We care deeply about fostering an environment where everyone is supported and can do their best work. SoundHound will ensure that individuals with disabilities are provided reasonable accommodations to participate in the interview process, perform essential job functions, and receive other employment benefits.
Employees enjoy comprehensive health care, paid time off, discounted fitness classes, and flexible working hours. Learn more about our philosophy, benefits, and culture at https://soundhound.com/careers/.
To view our job applicant privacy policy, please visit https://static.soundhound.com/corpus/ta/applicantprivacynotice.html.
Come join our growing team and bring your unique voice to our mission!
Tags: Ansible Computer Science Deep Learning DevOps Distributed Systems GPU Kubernetes Machine Learning MLFlow ML models Model training NLP Terraform
Perks/benefits: Career development Equity Flex hours Flex vacation Health care
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